The TLC Cybersecurity Simulation is a full day event to be held at Dobbins Air Reserve Base in Marietta, Georgia within the state-of-the-art facility of the Georgia Air National Guard Cybercommand. The event can also be made available via HD digital video streaming at AMC Theaters and Regal Cinemas throughout North America to companies with larger groups who would like to participate remotely. The event begins with a Morning Briefing (9am to noon EST) that will provide critical background information key to understanding the TLC Scenario and afternoon simulation. Following is a lunch for those attending the Morning Briefing and afternoon simulation. From 1:00pm to 3:00pm EST is the Cybersecurity Simulation that will provide an immersive experiential learning experience to help attendees understand, prepare for, and address cybersecurity issues in their own work environments. Lessons Learned (3:00 pm to 4:00 pm EST) is a discussion forum for what was learned from the Cybersecurity Simulation and a Recovery Reception (4:00 pm to 6:00 pm) serves as an opportunity for the on-stage role players and audience to mix, mingle and network while discussing the day's events and any open questions.
What does the TLC Scenario hold in store? What will we learn? What will happen? We don't know yet, but we do know that the TLC Scenario event will follow the same general format as 2013's highly successful GNN Scenario. Read the details leading up to the GNN attacks, a description of the simulation and the 2013 GNN After Action Report at the official website http://cyberexercises.com/tag2014/.
As a TAG affiliate and supporter, the Georgia Tech Supply Chain & Logistics Institute is able to provide a special discount off the registration fee. Please email web@scl.gatech.edu to have GTSCL reply with our event discount code and instructions on how to register online.
]]>SPEAKER: Dr. Jeff Wu
ABSTRACT:
Tukey has made wide-ranging contributions to statistics and other branches of science. Much less known is his early and unpublished work on experimental design. I will start my talk with his work on the jackknife and how it influenced Efron's work on the bootstrap. Also little known is that the core technical idea of his path-breaking work on Fast Fourier Transform (FFT) was rooted in experimental design, i.e., use of the Yates' algorithm. His unpublished work on studentized maximum modulus test was "rediscovered" in the Wu-Hamada book. His 1959 unpublished notes called "Little pieces of mixed factorials" was absolutely ahead of his time. I will explain some novel ideas in the notes and relate them to later development in design construction and speculate how it could have made even more impact.
(Notes: I gave this talk in the spring of 2000 a few months before his death. The talk was part of a one-day celebration of Tukey in the ASA New Jersey chapter. He was in the audience. Some of the contents of this talk remain fresh to these days. It speaks volumes about Tukey's ever lasting impact.)
]]>January 24, 2014
It starts at 10:30 am in the Student Ctr Theater with the Leadership and Ethics group ( 110 students - 8th through 12th grade) and the STEM 7th graders will go to the SLC 126 in ISyE Main.
The West Point Society of Atlanta in conjunction with ISyE will host the United States Military Academy's first ever Leadership, Ethics, and Diversity in STEM (LEADS) Conference for 7th - 12th graders and their faculty. The keynote speaker is United States Army (Ret.) Major General Ronald Johnson, West Point Class of 1976 and professor of practice and ISyE, who served at the highest ranks of Army leadership in peace and war. In addition to sharing his experience and views on ethical character in leadership, MG Johnson is a major sponsor for this workshop and one who will challenge you in your learning and your demonstration of leadership.
SPEAKER: Mladen Kolar
ABSTRACT:
Extracting knowledge and providing insights into the complex mechanisms underlying noisy high-dimensional data sets is of utmost importance in many scientific domains. Networks are an example of simple, yet powerful tools for capturing relationships among entities over time. For example, in social media, networks represent connections between different individuals and the type of interaction that two individuals have. In systems biology, networks can represent the complex regulatory circuitry that controls cell behavior. Unfortunately the relationships between entities are not always observable and need to be inferred from nodal measurements.
I will present a line of work that deals with the estimation of high-dimensional dynamic networks from limited amounts of data. The framework of probabilistic graphical models is used to develop semiparametric models that are flexible enough to capture the dynamics of network changes while, at the same time, are as interpretable as parametric models. In this framework, estimating the structure of the graphical model results in a deep understanding of the underlying network as it evolves over time. I will present a few computationally efficient estimation procedures tailored to different situations and provide statistical guarantees about the procedures. Finally, I will demonstrate how dynamic networks can be used to explore real world systems.
]]>Where: ISyE Main Bldg, Executive Classroom (Room 228) and ISyE Atrium
When: Wednesday, February 5th, 1:45-5PM
What: A half-day event that will include:
Please plan on staying for the duration of the event and bring copies of your resume and business cards. Dress is business casual.
The event is sponsored through the generosity and support of APICS - Atlanta Chapter. APICS is a non-profit educational organization addressing operations management and supply chain management issues, and providing professional development opportunities to our members. Visit http://www.apicsatlanta.org/ to learn more and make sure to stop by the APICS table at the event.
]]>Where: ISyE Main Bldg, Executive Classroom (Room 228) and ISyE Atrium
When: Friday, March 7th, 1:45-5:30PM
What: A half-day event that will include:
Please plan on staying for the duration of the event and bring copies of your resume and business cards. Dress is business casual.
The event is sponsored through the generosity and support of APICS - Atlanta Chapter. APICS is a non-profit educational organization addressing operations management and supply chain management issues, and providing professional development opportunities to our members. Visit http://www.apicsatlanta.org/ to learn more and make sure to stop by the APICS table at the event.
]]>SPEAKER: Professor Jack Hu
ABSTRACT:
Advanced manufacturing has been the buzz recently. What is advanced manufacturing? How can researchers in academia contribute to it? I offer my personal perspectives on this important topic and discuss challenges and opportunities in advanced manufacturing research and innovation. Several case studies will be used to illustrate how scientific methods and technological innovations can be translated into factory implementations.
S. Jack Hu was appointed the Interim Vice President for Research at the University of Michigan, effective January 1, 2014. He is also Professor of Mechanical Engineering, Professor of Industrial and Operations Engineering, and the J. Reid and Polly Anderson Professor of Manufacturing Technology in the College of Engineering.
Bio:
As the Vice President for Research, Dr. Hu has overall responsibility for nurturing the excellence and integrity of research across the entire campus. He oversees the U-M Office of Research, which promotes interdisciplinary research, develops and implements research policy, provides central administrative services in support of faculty research, innovation, and economic outreach, and manages activities related to compliance and the responsible conduct of research. Before his current appointment, Dr. Hu served as Associate Dean for Academic Affairs (2009–2013) and Associate Dean for Research and Graduate Education (2007–2009), both in the College of Engineering at the University of Michigan.
Dr. Hu’s teaching and research interests include manufacturing systems design and operations, assembly modeling, and statistical quality methods. He is the recipient of various awards, including the SME Outstanding Young Manufacturing Engineer Award, National Science Foundation CAREER Award, ASME William T. Ennor Manufacturing Technology Award, the College of Engineering Research Excellence Award, and several best paper awards. He is a fellow of the American Society of Mechanical Engineers (ASME) and a fellow of the International Academy for Production Engineering (CIRP). He served as the Editor in Chief of Journal of Manufacturing Systems from 2008 to 2013.
Dr. Hu received his B.S. from Tianjin University, China in 1983, M.S. and Ph.D. from the University of Michigan in 1986 and 1990 respectively.
]]>SPEAKER: David Brown
ABSTRACT:
We consider the information relaxation approach for calculating performance bounds for stochastic dynamic programs (DPs). This approach generates performance bounds by solving problems with relaxed nonanticipativity constraints and a penalty that punishes violations of these nonanticipativity constraints. In this paper, we study DPs that have a convex structure and consider gradient penalties that are based on first-order linear approximations of approximate value functions. When used with perfect information relaxations, these penalties lead to subproblems that are deterministic convex optimization problems. We show that these gradient penalties can, in theory, provide tight bounds for convex DPs and can be used to improve on bounds provided by other relaxations, such as Lagrangian relaxation bounds. Finally, we apply these results in two example applications: first, a network revenue management problem that describes an airline trying to manage seat capacity on its flights; and second, an inventory management problem with lead times and lost sales. These are challenging problems of significant practical interest. In both examples, we compute performance bounds using information relaxations with gradient penalties and find that some relatively easy-to-compute heuristic policies are nearly optimal. (Joint work with Jim Smith at Duke.)
]]>The conference program features plenary panels and interactive educational workshops to encourage discourse among participants, innovative research poster sessions, and ample time for networking, facility tours, and other activities. Ideas will be shared around emerging themes such as market mechanisms for food assistance, the vaccination supply chain in global public health, infrastructure needs for coordination and collaboration and end-to-end supply chain strategy. You are welcome to email your ideas for panel themes, workshop topics, and potential speakers/facilitators to humlog2014@mit.edu, loghumanitaria.csf@servicios.itesm.mx or humlogconf@gatech.edu.
Last year’s conference, held in Kuala Lumpur, drew participants from 25 countries from organizations such as Aidmatrix, CARE, the Salvation Army and The UN World Food Programme to Bader-Gateway, GlaxoSmithKline, Nanyang Technological University and USAID. Panel speakers and workshop facilitators in previous years have included leaders from The International Federation of the Red Cross/Red Crescent, Doctors Without Borders, John Snow Inc., Partners in Health, the World Bank and the World Health Organization.
This year’s conference has again been made possible by the generous support of the UPS Foundation and Georgia Tech. If your organization would like to co-sponsor the 2014 Health and Humanitarian Logistics Conference, please contact the conference organizers at one of the above email addresses.
We hope to see you in June 2014!
]]>SPEAKER: Professor Art Owen, Stanford University
ABSTRACT:
Sobol' indices are used to measure the importance of variables, and subsets of variables, in black box models of deterministic functions. They have strong connections to both experimental design and quasi-Monte Carlo sampling. This talk will review the functional ANOVA, define Sobol' indices and present some recent developments for them: improved algorithms, generalizations to higher order moments, and connections to Shapley value.
]]>Title: Confidence regions and confidence intervals for stochastic variational inequalities via the normal map approach
Abstract:
Variational inequalities model a general class of equilibrium problems, and also arise as first-order conditions of nonlinear programs. This talk considers a stochastic variational inequality (SVI) defined over a polyhedron, with the function defining the variational inequality being an expectation function. A basic approach for solving the SVI is the sample average approximation (SAA) method, which replaces the expectation function by a sample average function, and solves the obtained SAA problem to use its solution as an estimate of the true solution. It is well known that under appropriate conditions the SAA solutions provide asymptotically consistent point estimators for the true solution to an SVI.
We consider the normal map formulation of the SVI and the SAA problems, and discuss methods to compute confidence regions and confidence intervals of prescribed level of significance for the true solution, given an SAA solution. These methods are based on the asymptotic distribution of SAA solutions, obtained from combining sensitivity analysis techniques with suitable central limit results. The discontinuity of certain quantities causes a difficulty in estimating a function that governs the asymptotic behavior of SAA solutions. The piecewise linear property of the latter function leads to an additional difficulty in computing confidence intervals. This talk presents methods proposed to overcome those difficulties, with numerical results.
]]>This day and a half executive business forum is designed for business decision-makers, strategic business planners, consultants and senior academics interested in the business opportunities and profit potential afforded by the rapid expansion and globalization of India's Supply Chain.
PRESENTING PARTNERS
UIBS, Georgia Ports Authority, Georgia Tech CIBER and USIBRC
SUPPORTING PARTNERS
The U.S. Commercial Service (CS), The Georgia Department of Economic Development (GDEcD), Consulate General of India – Atlanta, The Metro Atlanta Chamber (MAC), World Trade Center – Savannah, Confederation of Indian Industry (CII), Georgia Tech Supply Chain and Logistics Institute (SCL), Emirates Airlines and Habif, Arogeti & Wynne, LLP
TUESDAY APRIL 15, 2014
WEDNESDAY, APRIL 16, 2014
Fireside Chat with CEO's
Confirmed/Invited* (as of March 12, 2014)
Many other representatives of partnering organizations...
]]>SPEAKER: Giovanni Motta
ABSTRACT:
Our approach for fitting dynamic nonstationary factor models to multivariate time series is based on the principal components of the estimated time-varying spectral-density matrix.
This approach allows the spectral matrix to be smoothly time-varying, which imposes very little structure on the moments of the underlying process. However, the estimation delivers time-varying filters that are high-dimensional and two-sided. Moreover, the estimation of the spectral matrix strongly depends on the chosen bandwidths for smoothing over frequency and time.
As an alternative, we propose a new semi-parametric approach in which only part of the model is allowed to be time-varying. More precisely, the latent factors admit a dynamic representation with time-varying autoregressive coefficients while the loadings are constant over time.
Estimation of the model parameters is accomplished by application of the EM algorithm and the Kalman filter. The time-varying parameters are modeled locally by polynomials and estimated by maximizing the likelihood locally. Compared to estimation of the factors by principal components, our new approach produces superior results in particular for small cross-sectional dimension.
]]>SPEAKER: Professor Eugene Feinberg, Stony Brook University
ABSTRACT:
Partially Observable Markov Decision Processes (POMDPs) describe control of stochastic systems whose current states are unknown and information about them is available only via indirect observations. They have a large spectrum of applications to various fields including operations research, electrical engineering, and computer science. In principle, a POMDP can me reduced to a Markov Decision Process (MDP) whose states are belief probabilities, that is, probability distributions on the set of all possible states. Such auxiliary MDPs are called Completely Observable MDPs (COMDPs).
If an optimal policy is found for the COMDP, it is easy to construct an optimal policy for the POMDP. However, the existence of optimal policies for COMDPs (and therefore for POMDPS) and their characterizations via optimality equations have been studied in the literature mainly for problems with finite state sets. Except a few cases, infinite-state problems have been considered only for particular applications. For the expected total costs criteria, we describe natural sufficient conditions for the existence of optimal policies for infinite-state POMDPs and derive optimality equations. The results presented in this talk are based on the recent progress in the analysis of infinite-state MDPs with weakly continuous transition probabilities, which were motivated by applications of MDPs to inventory control, and on new results on continuity properties of Bayes’s formula.
The talk is based on joint work with P.O. Kasyanov and M.Z. Zgurovsky.
Bio:
Eugene A. Feinberg received Ph.D. in Probability and Statistics from Vilnius University, Lithuania, in 1979. Between 1976 and 1988 he held research and faculty positions in the Department of Applied Mathematics at Moscow University of Transportation. After holding a one-year visiting faculty position at Yale University in 1988-89, he joined Stony Brook University, where Dr. Feinberg is currently Distinguished Professor at the Department of Applied Mathematics and Statistics.
His research interests include stochastic models of Operations Research, Markov Decision Processes, and industrial applications of Operations Research and Statistics. Since 1999, he has been working on electric energy applications. He has published more that 130 papers and edited the Handbook on Markov Decision Processes. His research is partially supported by the National Science Foundation, Department of Energy, New York Office of Science, Technology and Academic Research (NYSTAR), New York State Energy Research and Development Authority (NYSERDA), and industry. He is a member of several editorial boards including Mathematics of Operations Research, Operations Research Letters, and Applied Mathematics Letters. He has been awarded Honorary Doctorate from the Institute of Applied System Analysis, National Technical University of Ukraine. Dr Feinberg is a Fellow of INFORMS (The Institute for Operations Research and Management Sciences), a recipient of 2012 IEEE Charles Hirsh Award “For developing and implementing on Long Island, electric load forecasting methods and smart grid technologies,” and a recipient of 2012 IBM Faculty Award.
]]>Where: ISyE Main Bldg, Executive Classroom (Room 228) and ISyE Atrium
When: Wednesday, April 9th, 1:45-5:00PM
What: A half-day event that will include:
Please plan on staying for the duration of the event and bring copies of your resume and business cards. Dress is business casual.
The event is sponsored through the generosity and support of APICS - Atlanta Chapter. APICS is a non-profit educational organization addressing operations management and supply chain management issues, and providing professional development opportunities to our members. Visit http://www.apicsatlanta.org/ to learn more and make sure to stop by the APICS table at the event.
]]>Free food/games/T-Shirts/Music/Giveaways/Photo Booth
Please plan to come to enjoy food, and fun activities with the students.
]]>SPEAKER: Peter Frazier, Cornell University
ABSTRACT:
We consider information filtering, in which we face a stream of items too voluminous to process by hand (e.g., scientific articles, blog posts, emails), and must rely on a computer system to automatically filter out irrelevant items. Such systems face the exploration vs. exploitation tradeoff, in which it may be beneficial to present an item despite a low probability of relevance, just to learn about future items with similar content. We present a Bayesian sequential decision-making model of this problem, and provide a decomposition technique that allows solving the resulting Markov decision process to optimality. We show that the resulting method is especially useful when facing the cold start problem, i.e., when filtering items for new users without a long history of past interactions. We then present initial results from an ongoing rollout of this information filtering method for an influential repository of scientific articles, arXiv.org.
]]>SPEAKER: Karen Aardal
ABSTRACT:
In the transportation problem with market choice we are given a set of markets with demands and a set of facilities with limited capacities in a common metric space. Each market is either accepted or rejected. For each accepted market, its demand has to be fully satisfied by facilities, which incurs transportation cost. For each rejected market, a penalty cost has to be paid. The goal is to decide which markets should be accepted and which should be rejected, such that the sum of transportation and penalty cost is minimized.
The transportation problem with market choice was introduced by Damci-Kurt, Dey, and Küçükyavuz, who show that TPMC is NP-hard, and examine the polyhedral structure. Here we derive a constant factor approximation algorithm based on local search.
This is joint work with Pieter van den Berg and Shanfei Li.
]]>SPEAKER: Yuri Nesterov
ABSTRACT:
In this talk, we present new subgradient methods for solving nonsmooth
convex optimization problems. These methods are the first ones, for which
the whole sequence of test points is endowed with the worst-case performance
guarantees. The methods are derived from a relaxed estimating sequences
condition, and ensure reconstruction of an approximate primal-dual optimal
solutions.
Our methods are applicable as efficient real-time stabilization tools for
potential systems with infinite horizon. As an example, we consider a model
of privacy-respecting taxation, where the center has no information on the
utility functions of the agents. Nevertheless, by a proper taxation policy,
the agents can be forced to apply in average the socially optimal
strategies. Preliminary numerical experiments confirm a high efficiency
of the new methods.
This is a joint work with V.Shikhman (CORE).
SPEAKER: Alan Scheller-Wolf, Carnegie Mellon
ABSTRACT:
All service facilities, from small restaurants to large call centers, are concerned about the quality of service (QoS) they provide to their customers. However, capacity planning for service systems is often difficult, for example, due to impatient customers who are likely to abandon a facility when the system is congested. An important, yet simple rule-of-thumb to identify the ideal staffing level that satisfies a desired QoS level is the square-root staffing rule, derived from the Erlang A model. However, to apply the rule, we need to assume that arrival/service rates are relatively stable throughout the planning period. This may not be true when managers can control the arrival rate and/or the service rate during congestion. We call such measures congestion-based control (CBC) schemes. We derive non-asymptotic and asymptotic representations of performance indicators for an Erlang A model under CBC.
Joint work with Kats Sasanuma and Robert Hampshire, Heinz School, Carnegie Mellon University.
BIO:
Alan Scheller-Wolf is a Professor of Operations Management at the Tepper School of Business, where he also serves as head of the PhD program. He received his PhD from the IE/OR department of Columbia University in 1996, having completed his doctorate under the advising of Karl Sigman. He has a Bachelor of Science in Mathematics and Computational Science, and a Bachelor of Arts in Art History, from Stanford University. Prior to his time at Columbia, Alan served for 2 1/2 years in the Peace Corps as a mathematics teacher, in Serowe, Botswana.
Alan's research interests include inventory theory (especially ATO systems, systems with capacities, alternate supply options and/or perishable products), energy, service systems, computer science, stochastic processes and queueing theory. He sits on the editorial boards of Management Science, Operations Research, M&SOM, MMOR, and QUESTA. He has completed consulting projects with Amazon, Caterpillar, John Deere, The American Red Cross, and The Vera Institute of Justice. He currently teaches MBA courses in Quality and Sustainable Operations.
]]>SPEAKER: Cristobal Guzman
ABSTRACT:
We prove lower bounds on the black-box oracle complexity of large-scale
smooth convex minimization problems. These lower bounds work for unit balls
of normed spaces under a technical smoothing condition, and arbitrary
smoothness parameter of the objective with respect to this norm. As a
consequence, we show a unified framework for the complexity of convex
optimization on \ell^p-balls, for 2<=p<=\infty. In particular, we prove
that the T-step Conditional Gradient algorithm as applied to minimizing
smooth convex functions over the n-dimensional box with T<=n is nearly
optimal.
On the other hand, we prove lower bounds for the complexity of convex
optimization over \ell^p-balls, for 1<=p<2, by combining a random subspace
method with the p=\infty lower bounds. In particular, we establish the
complexity of problem classes that contain the sparse recovery problem.
This is joint work with Arkadi Nemirovski
Today's digital consumer wants "what they want, when they want it, delivered to wherever they will be"...that is the new paradigm challenge for retail supply chain executives. Effectively managing supply chains for this fast growing "omni-channel" consumer behavior is requiring supply chain and IT executives to reconsider how they leverage their physical assets, inventory, and information. Our panel will discuss the best practices and lessons learned for managing "omni-channel" order fulfillment and delivering for this fast growing marketplace.
Panelists from: Oracle, Peach State Integrated Technologies and UPS
Register Today!
TAG members: $25; Non-members $40
For more information and to register online, please visit bitly.com/tagomnichannel.
Sponsors
Gold: Pyramid Consulting
Silver: Catavolt, Primus Software Corporation, Software AG Suite
SPEAKER: Mariel Lavieri
ABSTRACT:
Chronic disease management often involves sequential decisions that have long-term implications. Those decisions are based on high dimensional state spaces, which pose a problem for traditional modeling paradigms. In some key instances, transition probabilities might not be known, but instead are random variables that are learned as new information becomes available.
As a first step, I describe some of my ongoing research modeling screening, monitoring and treatment decisions of patients with chronic conditions. The models are motivated by diseases such as glaucoma, coronary heart disease and cancer. Key to the models developed is the incorporation of the individual patient's disease dynamics into the parameterization of the stochastic models of the disease state evolution. Model conception and validation is described, as well as the role of multidisciplinary collaborations in ensuring practical impact of my work.
]]>Where: Technology Square Research Building
When: Thursday, May 29, 2014, 3:30 p.m. – 6:00 p.m.
The Panama Canal expansion, scheduled for completion in 2015, is expected to dramatically increase the flow of goods through east and gulf coast ports. Join the discussion exploring what this will mean for roadway transportation infrastructure nationwide. Researchers from the Center for Quality Growth and Regional Development at the Georgia Institute of Technology will share the results of their work analyzing the impact of the expansion on the volume of commodity movement, trucking route choice, economic impact and how federal, state, and local government is planning to accommodate future freight needs. Following the presentation, panelists will discuss the service impact of shifting cargo to bigger ships and the net effects of either driving shipping to or from the U.S. East Coast ports.
Panelists from: Panama Gateway International Association, Georgia Tech Center for Quality Growth and Regional Development, Georgia Ports Authority and the Georgia Tech Panama Logistics Innovation & Research Center
TAG members: $25; Non-members $40
For more information and to register online, please visit http://bit.ly/tagpanama.
Gold: Pyramid Consulting
Silver: Catavolt, Primus Software Corporation, Software AG Suite, Georgia Tech Supply Chain & Logistics Institute
Georgia Tech Research Institute, 250 14th Street, NW, Atlanta, GA 30318
$10 per person, includes food and drinks
Register now!
Join us for an evening of All Industry networking with entrepreneurs and business leaders hosted by the Alumni Affinity Groups. Then, catch a lively Fireside Chat with keynote speaker John Marshall, Vice President and General Manager of AirWatch by VMware on the Entrepreneurial Journey: From Georgia Tech to a Billion Dollar Acquisition.
John Marshall started AirWatch by VMware by running Cat-5 cable behind grease vats at local coffee shops for WiFi hotspots. His story has now become an influential startup success story and a clear example for others looking to disrupt industries. After the iPhone emerged, AirWatch by VMware’s focus shifted to help organizations manage mobile devices for business use. Under Marshall’s leadership, AirWatch by VMware has become the world’s leading Enterprise Mobility Management (EMM) provider with exponential growth in the past three years, increasing employees from 150 to 1,600 and securing 10,000 global customers.
Marshall will share his story, provide insight on how you can launch and grow a successful company, and offer his view of global trends and business growth areas. Don’t miss this must-see program featuring this world renowned business leader.
Market your business at BizTech 2014!
$100
Register now!
We will market your logo and website on all marketing before and during the event. Also, receive a complimentary session on “Real World Retirement Planning for Business Owners,” sponsored by Apex Financial.
6-7 p.m. – Check-in and networking
7-7:25 p.m. – Keynote address by John Marshall
7:25-8:05 p.m. – Fireside Chat with John Marshall
8:05-8:30 p.m. – Q&A
8:30 – 9:00 p.m. – Networking and Adjourn
STUDENT: Soheil Shayegh
ADVISOR: Dr. Valerie Thomas
SUMMARY:
In this research we study learning in optimization models with uncertainty. The focus is on applications of adaptive stochastic programming in integrated assessment modeling of climate change and economy.
In the first part of the thesis we investigate finite horizon stochastic models with continuous state and action space. We develop an approximation technique for calculating the value function endogenously and in an online fashion. We introduce a multistep lookahead value iteration algorithm to update the parameters of the approximation function. We apply this technique to a dynamic integrated assessment model of climate change and economy. We present the results of our analysis in both deterministic and stochastic cases. We show that the multistep ahead approximation technique is capable of approximating the value function fast and converging to its true value. We study the optimal behavior of the model under uncertainty from climate parameters and shocks. We show how a stochastic model can inform climate mitigation decisions when there is risk of an extreme event, with larger actions before an extreme event, and potentially smaller actions after.
The second part of the thesis looks at stochastic models with correlated uncertainties. We address the correlation between uncertain temperature increase and contingent climate extreme events. As temperature increases so does the chance of having an extreme event. The occurrence of an extreme event provides information about the distribution of the temperature controlling parameter. We address this correlation through Bayesian inference. We apply an automatic update to our previous algorithm and show how the posterior distribution of the control parameter is updated as we receive more information about the realization of the dependent parameter through simulation. We show how the optimal solution varies as learning happens over time and updates the prior probability distributions.
In the third part of the thesis, we explore a different aspect of learning: learning-by-doing. We consider the global electricity generation expansion planning problem with or without climate regulations. We model a spectrum of electricity generation technologies with different emissions, costs, and learning rates. We show how the optimal mix of technologies varies under different climate regulatory regimes. The optimal solution also depends on the learning assumption and the social time preference factor (discounting). We see that in both cases, with or without climate regulations, new technologies enter the optimal portfolio if the learning is applied to the model. We also compare the results in terms of impact on the global mean surface temperature and show that early investment in new low carbon technologies can lower the long-term temperature trajectory.
]]>STUDENT: Melih Celik
ADVISORS: Dr. Ozlem Ergun and Dr. Pinar Keskinocak
SUMMARY:
In this thesis, we consider three applications of humanitarian, emergency response and public health supply chains, namely (i) debris management, (ii) allocation of perishable commodities, and (iii) specialized nutritious foods supply chain design, where the main decisions relate to the allocation of scarce resources and there is inherent uncertainty in the environment. Our particular focus is on incorporating stochasticity into the models that address these decisions and making use of information updates as they become available.
Debris management is one of the most time consuming and complicated activities among post-disaster operations. Debris clearance is aimed at pushing the debris to the sides of the roads so that relief distribution and search-and-rescue operations can be maintained in a timely manner. In the first part of the thesis, we define the stochastic debris clearance problem (SDCP), which captures post-disaster situations where there is limited information on the debris amounts on the roads and the information is updated as clearance activities proceed. We propose a partially observable Markov decision process (POMDP) model to solve SDCP to optimality. Due to the extensive computational requirements of the POMDP model, we propose a heuristic based on a continuous time approximation, and further reduce the computational burden by applying a limited look-ahead on the search tree and using heuristic pruning. The performance of these approaches is tested on randomly generated instances that reflect various geographical and information settings and instances based on a real world earthquake scenario.
Motivated by a public health supply chain problem, we consider the allocation of a perishable item in a decentralized supply chain in the second part of the thesis. The supply chain consists of two levels: a capacitated allocation center upstream and multiple distribution locations downstream. Each distribution location serves multiple demand types with varying unit benefits accrued from satisfying the demand, and applies a certain usage policy to satisfy the uncertain demand. In particular, we focus on prioritization of higher-class demand and first-come, first-served (FCFS) usage policies. Under the assumption of no reallocation, we develop myopic algorithms that find the optimal allocation that maximizes the expected net benefit for the system. When demand arrivals follow a Poisson process, we establish a worst-case bound on the relative performance of optimal allocation under FCFS compared to that under prioritization. We also show that centralization, i.e., serving a certain demand class or all demand from a single location, can guarantee the improvement of expected net benefit over a decentralized system only if demand is prioritized and completely served from a single location. We compare the relative performances of the two usage policies, assess the effects of centralization, and compare our approaches to simpler allocation schemes using computational experiments from a dataset based on the 2009 H1N1 vaccination campaign in the state of Georgia.
Specialized nutritious foods (SNF) are aimed at the prevention and treatment of undernutrition, which leads to irreversible and long-term consequences such as hampering of body growth and reduction in productivity. Certain aspects of SNF, such as high product value, low shelf life, geographical disparity of supply and demand, limited visibility into the supply chain, and the need for refrigeration pose important challenges for efficient supply chain management. In the last part of this thesis, we present a case study on the SNF supply chain of a large scale humanitarian organization, where the aim is to determine the network structure and optimal allocation of these commodities to the distribution locations. We develop mixed integer programming models for determining the facility locations, incorporation of information updates, and equity of allocations. Using computational experiments based on data from the organization, we determine aspects of the system that have the most significant impact on the selection of network structure, and show the impact of incorporating uncertainty and information updates to our models.
]]>STUDENT: Aly Megahed
ADVISOR: Dr. Marc Goetschalckx
SUMMARY:
In this thesis, we study three supply chain planning problems. The first two problems fall in the tactical planning level, while the third one falls in the strategic/tactical level. We present a direct application for the first two planning problems in the wind turbines industry. For the third problem, we show how it can be applied to supply chains in the food industry.
Many countries and localities have the explicitly stated goal of increasing the fraction of their electrical power that is generated by wind turbines. This has led to a rapid growth in the manufacturing and installation of wind turbines. The globally installed capacity for the manufacturing of different components of the wind turbine is nearly fully utilized. Because of the large penalties for missing delivery deadlines for wind turbines, the effective planning of its supply chain has a significant impact on the profitability of the turbine manufacturers. Motivated by the planning challenges faced by one of the world’s largest manufacturers of wind turbines, we present a comprehensive tactical supply chain planning model for manufacturing of wind turbines in the first part of this thesis. The model is multi-period, multi-echelon, and multi-commodity. Furthermore, the model explicitly incorporates backorder penalties with a general cost structure, i.e., the cost structure does not have to be linear in function of the backorder delay. To the best of our knowledge, modeling-based supply chain planning has not been applied to wind turbines, nor has a model with all the above mentioned features been described in the literature. Based on real-world data, we present numerical results that show the significant impact of the capability to model backorder penalties with general cost structures on the overall cost of supply chains for wind turbines.
With today’s rapidly changing global market place, it is essential to model uncertainty in supply chain planning. In the second part of this thesis, we develop a two-stage stochastic programming model for the comprehensive tactical planning of supply chains under supply uncertainty. In the first stage, procurement decisions are made while in the second stage, production, inventory, and delivery decisions are made. The considered supply uncertainty combines supplier random yields and stochastic lead times, and is thus the most general form of such uncertainty to date. We apply our model to the same wind turbines supply chain. We illustrate theoretical and numerical results that show the impact of supplier uncertainty/unreliability on the optimal procurement decisions. We also quantify the value of modeling uncertainty versus deterministic planning.
Supplier selection with quantity discounts has been an active research problem in the operations research community. In this the last part of this thesis, we focus on a new quantity discounts scheme offered by suppliers in some industries. Suppliers are selected for a strategic planning period (e.g., 5 years). Fixed costs associated with suppliers selection are paid. Orders are placed monthly from any of the chosen suppliers, but the quantity discounts are based on the aggregated annual order quantities. We incorporate all this in a multi-period multi-product multi-echelon supply chain planning problem and develop a mixed integer programming (MIP) model for it. Leading commercial MIP solvers take 40 minutes on average to get any feasible solution for realistic instances of our model. With the aim of getting high-quality feasible solutions quickly, we develop an algorithm that constructs a good initial solution and three other iterative algorithms that improve this initial solution and are capable of getting very fast high quality primal solutions. Two of the latter three algorithms are based on MIP-based local search and the third algorithm incorporates a variable neighborhood search (VNS) combining the first two. We present numerical results for a set of instances based on a real-world supply chain in the food industry and show the efficiency of our customized algorithms. The leading commercial solver CPLEX finds only a very few feasible solutions that have lower total costs than our initial solution within a three hours run time limit. All our iterative algorithms well outperform CPLEX. The VNS algorithm has the best average performance. Its average relative gap to the best known feasible solution is within 1% in less than 40 minutes of computing time.
STUDENT: Huan Yan
ADVISOR: Roshan Vengazhiyil
SUMMARY:
This thesis consists of three chapters, covering topics from the adjustment, calibration and uncertainty quantification of computer models to their applications in cardiac cell modeling and uncertainty propagation in machining process. The first chapter systematically develops an engineering-driven statistical adjustment and calibration framework, and the second chapter is devoted to the calibration of potassium current model in a cardiac cell. The third chapter proposes a novel emulator for approximating the complex computer model in the analysis of uncertainty propagation.
Engineering model development involves several simplifying assumptions for the purpose of mathematical tractability which are often not realistic in practice. This leads to discrepancies in the model predictions. A commonly used statistical approach to overcome this problem is to build a statistical model for the discrepancies between the engineering model and observed data. In contrast, an engineering approach would be to find the causes of discrepancy and fix the engineering model using first principles. However, the engineering approach is time consuming, whereas the statistical approach is fast. The drawback of the statistical approach is that it treats the engineering model as a black box and therefore, the statistically adjusted models lack physical interpretability. In the first chapter, we propose a new framework for model calibration and statistical adjustment. It tries to open up the black box using simple main effects analysis and graphical plots and introduces statistical models inside the engineering model. This approach leads to simpler adjustment models that are physically more interpretable. The approach is illustrated using a model for predicting the cutting forces in a laser-assisted mechanical micromachining process and a model for predicting the temperature of outlet air in a fluidized-bed process.
The second chapter studies the calibration of a complex computer model that describes the potassium currents in a cardiac cell. The computer model is expensive to evaluate and contains 24 unknown calibration parameters, which makes the problem very challenging for the traditional methods of calibration using kriging. We propose physics-driven strategies for the approximation and calibration of this large-complex model. Another difficulty with this problem is the presence of large cell-to-cell variation, which is modeled through random effects. We propose approximate Bayesian methods for the identification and estimation of the parameters in this complex nonlinear mixed-effects statistical model.
Monte Carlo and Quasi-Monte Carlo methods could be slow if the computer model is computationally expensive. An easy-to-evaluate metamodel is usually used to replace the computer model to improve the computational efficiency. However, the traditional metamodel could perform poorly for some complex system, e.g. the solid end milling process. In chapter three, we developed a new emulator, in which a base function is used to capture the general trend of the system and a discrepancy term to account for the remaining characteristics. We also proposed an optimal experimental design based on local input space for fitting the emulator. We call our proposed emulator local base emulator. In prediction, the simulation outputs with parameters at nominal values are used for the evaluation of base function. Linear function and Gaussian process are used for modeling the discrepancy. Through the solid end milling example, we show that the local base emulator is an efficient and accurate technique for uncertainty analysis and has obvious advantages over the other traditional tools.
STUDENT: Mallory Soldner
ADVISERS: Dr. Ozlem Ergun and Dr. Julie Swan
SUMMARY:
This thesis focuses on three topics relevant to humanitarian applications: (i) stable and complete assignment of staff members to field offices, (ii) bottleneck management for transportation networks, and (iii) performance measurement of the food assistance supply chain.
The assignment and reassignment of personnel to jobs is a large-scale problem faced by many organizations including the military and multi-national organizations. Although successful algorithms have been developed that can ensure matchings that are stable (without incentive to deviate), not all practical concerns have been addressed by these algorithms. For example, the gap we study is that when staff members do not provide preference lists covering all jobs, a complete stable matching is not guaranteed. In the first part of the thesis, we model negotiations, which occur in practice, as part of the problem of matching all agents. We introduce algorithms and structural results for when the organization negotiates with specific agents to modify their preference lists and the centralized objective is to minimize the number or cost of negotiations required to achieve complete stable matchings.
An uncertain environment with disruptions is a reality faced by many humanitarian operations but not fully addressed in the literature. Transportation delays are often driven by reliability issues (e.g., customs delays, strikes, and the availability of transport), and the length of wait time can be influenced by congestion. In the second part of the thesis, we describe a queuing model with breakdowns to model delays in port and transportation corridors (the overland travel from discharge ports to delivery points). Using the model, we gain insights into where delays are most detrimental to system performance (i.e., the network's ``bottleneck'') in port and transportation corridors. We then include our delay modeling in a convex cost network flow model that determines optimal routing when several port and corridor options are available. Finally, we examine a resource allocation model for where to invest in improvements to minimize delay. Throughout, we compare solutions using the optimal approach to rules of thumb and identify important factors that might be missing in practical decision making currently.
Third, we present a case study on the implementation of supply chain key performance indicators (KPIs) at a large humanitarian organization. We examine what is necessary for a full implementation of KPIs for the supply chain and the challenges of performance measurement at a humanitarian or non-profit institution, highlighting differences and similarities with the private sector.
STUDENT: Bahar Cavdar
ADVISOR: Dr. Joel Sokol
SUMMARY:
In this thesis, we study time sensitive applications where it is critical to minimize the completion time, i.e., the time passing between receiving the instance and finishing the implementation of the solution. In contrast to the traditional compute-first implement-later approach, we focus on the minimization of the computation time of the solution in addition to finding the best possible solution to the problem. We propose a new approach called Computation-Implementation Parallelization (CIP) and develop methods to embed the computation time into the solution-implementation to minimize the completion time. We implement our approach on the specific cases of the Traveling Salesman Problem (TSP) and Vehicle Routing Problem (VRP). We also present a TSP tour length estimation model that does not make any assumption on the distribution of the nodes.
In the first chapter, we implement our CIP approach on a type of TSP we call the TSP Race problem. In this problem setting, given the same graph and starting from the same point, two salesmen are racing to finish the tour before the other. The race starts as soon as the graphs are released to the salesmen. Therefore, how long they compute is also a factor determining who will win. We demonstrate CIP's effectiveness on TSP Race instances. We also demonstrate a method for determining a priori when CIP will be effective.
In the second chapter, we focus on large-scale parcel delivery. Making good routing decisions has become computationally more demanding due to both increasing size of the logistics operations and also the increasing trend in integrating the problems to make better decisions for the overall system. However, tight schedules in warehouses may allow only very limited time for computation for routing. To improve the solution quality, increasing the computation time may not be always feasible since it requires either shifting the order cutoff time to an earlier point in time or delaying the truck dispatching. To overcome this issue, using our CIP approach, we embed computation into the truck loading phase to create free-computation time.
Our research in CIP opened up a new question on TSP tour length estimators. Tour length estimations can be used to determine the quality of a tour on hand. Estimation models in the TSP literature focus on instances where the node dispersion is known (and often is uniform). In the third chapter, to deal with more general cases, i.e., graphs with non-uniform and unknown node dispersions, we develop a new empirical tour length estimation model for a broader dispersion family based on regression. Our model can estimate the tour lengths of these graphs to +/-3% of the tour length found by the Lin-Kernighan algorithm, with standard deviation of the estimation errors four times smaller than most previous models. When the distribution of the node coordinates is known, it can also estimate the coefficient of the well-known asymptotic tour length estimation formula of Beardwood et al. (1959), whose estimate cannot be computed if the node dispersion is not known. Our model not only produces good estimates on several different dispersion types, but also substitutes for Beardwood et al.'s estimation formula when the distribution is unknown.
]]>
Big data is gaining lot of buzz in healthcare. According to McKinsey Global Institute, the potential value of big data - if used creatively and effectively by the U.S. healthcare industry - is worth more than $300 billion per year. Currently healthcare providers are underutilizing 90% of that information. Please join us for networking and to learn from some of Atlanta's top innovators, researchers and data scientists. Hear how some of the country's largest healthcare providers are leveraging Big Data in Healthcare to improve patient outcomes.
Health 2.0 Atlanta is a meet up group focused on connecting the Atlanta healthcare technology community. Our meetings include a mix of company presentations, panel discussions and speakers from the services, payor/plan, and technology sub-sectors. We're also a great source for community announcements! Join today to stay current on local news, job opportunities and other health tech meetups. We encourage physicians, nurses, practice mangers, pharmacists, healthcare executives and social workers to actively participate.
Panelists include:
Dr. Nicoleta Serban
Georgia Institute of Technology
Author of Understanding & Managing the Complexity of Healthcare
Mike Thompson
Children's Healthcare of Atlanta
Vice President of Business Intelligence
Kirk Elder
WellCentive, Inc.
Chief Technology Officer
Michele Madison
Morris, Manning & Martin, LLP
Healthcare Partner
Andy Ibbotson - (moderator)
Digital Assent LLC
Founder & Chief Executive Officer
About Health 2.0 :: ATL
Health 2.0 Atlanta is a meetup group focused on connecting the Atlanta healthcare technology community. Our meetings include a mix of company presentations (from start-ups to public companies), panel discussions and speakers from the services, payor/plan, and technology sub-sectors. We're more than just a meetup group. We're also a great source for community announcements! Join today to stay current on local news, job opportunities and other health tech meetups. Please note that this group is not limited to technology enthusiasts. We encourage physicians, nurses, practice mangers, pharmacists, healthcare executives and social workers to actively participate.
Registration: http://www.meetup.com/Health-2-0-Atlanta/events/185641032/
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Where: Newell Rubbermaid Headquarters (3 Glenlake Parkway, NE, Atlanta, GA 30328)
When: Wednesday, September 10, 2014, 11:30 a.m. – 1:30 p.m.
The next big thing in supply and demand chain management is here – but what does it mean to different industries, how can it be leveraged, what’s out there now, and what’s the future outlook? Big Data techniques provide supply chain and IT executives with a means to tailor increasingly more complex global supply and demand chains through the smart use of data and analytics. Our panel will discuss the application of Big Data techniques for managing complex supply chains and developing competitive advantage.
Panelists from: Newell Rubbermaid, Peach State Integrated Technologies, Competitive Insights, Emcien and the Georgia Tech Supply Chain & Logistics Institute.
TAG members: $25; Non-members $40
For more information and to register online, please visit http://bit.ly/tagbigdata.
Gold: Pyramid Consulting
Silver: Catavolt, Georgia Tech Supply Chain & Logistics Institute, Insperity, Primus Software Corporation, Software AG Suite,
This free, one-hour webinar will introduce attendees to using proven principles of lean management to cut waste and improve warehouse efficiencies. Based on the Lean Warehousing professional education course offered through the Georgia Tech Supply Chain and Logistics Institute, Brad Bossence will discuss:
After attending this webinar, first-time attendees receive a promo code for a discount towards the "Lean Warehousing" course being taught on the Georgia Tech campus September 23 - 25, 2014!
Brad has over 15 years of third party logistics experience with a specific focus in Japanese production system environments such as Toyota USA, Toyota Canada, Toyota Europe, Kubota, Yamaha, Suzuki, and Subaru. His previous roles include General Manager of Logistics and Operations at Transfreight as well as various contract and operations management positions across the globe.
As Regional Vice President, Brad’s responsibilities have included the vision, leadership and momentum necessary for LeanCor to develop and significantly grow its global customer base. In addition, he has led on a variety of extensive customer projects. Brad is also a Senior Instructor at Georgia Tech Supply Chain and Logistics Institute. LeanCor is committed to continuous improvement and fully recognizes performance is measured by real results. As an operator and thought leader, LeanCor relentlessly tries to optimize those processes that add value and eliminate those that are waste.
]]>The efficient flow of inbound materials through your supply chain can have a significant impact on cost, quality, service, and delivery to your customer. With continued pressures from globalization, market volatility, and innovation expectations, companies are extending their reliance on lean principles to outside the four walls of the manufacturing facility. Lean inbound logistics requires strategic coordination to synchronize suppliers, transportation providers and multiple supply chain partners. And like all complex multi-party operations, the road to improvement will have its challenges. Such hurdles could include balancing inventory cost with transportation cost, the lack of leadership understanding and support, and the realities of incumbent manufacturing and procurement contracts and systems.
This free 1-hour webinar will focus on the why and how to implement lean logistics to support the lean supply chain operations – both in manufacturing and distribution. Areas of focus include: lean strategy development, identifying and overcoming operational realities, and learning about the tools necessary for successful implementation.
Brad Bossence, instructor for the GTSCL Lean Inbound Logistics course and Vice President at LeanCor Supply Chain Group will host the session.
After attending this webinar, attendees will receive a promo code for a discount towards the "Lean Inbound Logistics" course being taught in Savannah, GA September 29-30, 2014!
Learn more about the GTSCL Certificate Series at http://www.scl.gatech.edu/certificates.
Parents and guests are also invited and encouraged to attend and celebrate their student's entry into Georgia Tech. A special reception for parents and guests will be held immediately before the Convocation ceremony at the Georgia Tech Hotel & Conference Center. Parking will be available at the venue and a shuttle will provide transportation to the McCamish Pavilion. For more information, visit theParents Program website.
Immediately Following Convocation
Students will attend a special welcome party sponsored by Auxiliary Services - Rock, Ramble, and Roll - which celebrates their first night as a Georgia Tech college student. Held in the Student Center, students may take a shuttle or walk over after the Convocation ceremony. This is a free event for new students.
Laura Pusateri
Special Events & Protocol
404.894.7613
]]>Where: ISyE Main Bldg, Executive Classroom (Room 228) and ISyE Atrium
When: Tuesday, September 23rd, 11:00AM-2:00PM
What: The session will include:
Please plan on staying for the duration of the event and bring copies of your resume and business cards. Dress is business casual.
The event is sponsored through the generosity and support of APICS - Atlanta Chapter. APICS is a non-profit educational organization addressing operations management and supply chain management issues, and providing professional development opportunities to our members. Visit http://www.apicsatlanta.org/ to learn more and make sure to stop by the APICS table at the event.
]]>Doug Gray
Senior Manager, Optimization Solutions
Production Solutions Department, Technology
Southwest Airlines
Operations Research in the Airline Industry: A Survey with Specific Problem Modeling Formulations
Abstract:
Airlines represent logistically complex enterprises with many inter-related and inter-dependent business functions, e.g., flight schedules, crew schedules, and maintenance schedules. Airlines operate in a highly competitive domestic and global market place, selling what is, in effect, a commodity product to a highly price sensitive consumer. Airlines are also subject to various factors beyond their control that directly affect their operations, their On-Time Performance, their customer service levels and profitability, e.g., weather, FAA regulations, Air Traffic Control (ATC) delay programs, ground and air traffic congestion, labor union contracts. Airline operating costs are driven by fuel costs, highly skilled unionized labor costs, and maintenance costs. Airline capital expenditures are driven by aircraft costs, facilities, gate, and slot costs. Airline revenues are driven by markets served, competition-driving pricing, and optimally matching inventory supply to consumer demand. All of these factors combined make for a challenging airline operating environment.
Operations Research plays a significant and critically important role in analyzing and optimizing airline operations ranging from minimizing costs, maximizing revenue and profit, enhancing customer experience and satisfaction. We will review how OR factors into airline planning and operational business processes, and we will examine specific airline problem and solution modeling approaches.
Note that Doug is a GT alum, and he'll be here for a couple of days to recruit students at all levels.
]]>SPEAKER: Dr. Ping Ma, UGA
ABSTRACT:
Advances in science and technology in the past a few decades have led to big data challenges across a variety of fields. Extraction of useful information and knowledge from big data has become a daunting challenge to both the science community and entire society. To tackle this challenge requires major breakthroughs in efficient computational and statistical approaches to big data analysis. In this talk, I will present some leveraging algorithms, which make a key contribution to resolving the grand challenge. In these algorithms, by sampling a very small representative sub-dataset using smart algorithms, one can effectively extract relevant information of vast data sets from the small sub-dataset. Such algorithms are scalable to big data. These efforts allow pervasive access to big data analytics especially for those who cannot directly use supercomputers. More importantly, these algorithms enable massive ordinary users to analyze big data using tablet computers.
]]>SPEAKER: Kimia Ghobadi
ABSTRACT:
In this talk we explore automated inverse treatment planning for Gamma Knife Perfexion to treat head-and-neck tumours. The main goal in designing a treatment plan is to deliver an appropriate amount of dose to tumour structures while avoiding the surrounding healthy tissue as much as possible. In continuous dose delivery treatment planning, the radiation is delivered with a continuous beam along a path inside the tumour instead of the conventional method of using multiple discrete beams.
To obtain a quality treatment plan, we first use a set of approximation algorithms to find the position of the focal points of the shots inside the tumour volume. We then used these focal points to construct a path that covers the tumour volume. Once the path is selected, a
mixed-integer optimization model and its approximated linear model are formulated to find the beam intensity and duration for each point on the path. In this optimization model we minimize the dose spillage to healthy organs while ensuring the tumour receives the prescribed dose.
We impose additional clinical and machine constraints such as maximum dose to healthy organs, maximizing the utility of the available beams, speed constraints for the radiation unit, etc. We test our plan on clinical test cases and observe that the quality of the plans are better
or comparable with clinical treatment planning.
STUDENT: Min Kyu Sim
ADVISOR: Dr. Shijie Deng and Dr. Xiaoming Huo
SUMMARY:
This dissertation addresses the fundamental question of what factors moves stock prices and how they work, based on the two different frequency level of financial data. The first part concerns with daily or monthly frequency of data and aims to identify what systematic risk factor affects stock return. The second part concerns with data whose frequency is a second or even a millisecond, and aims to identify how the hidden supply-demand of a stock affects the stock price dynamics. With growing importance of quantitative models on financial data, we expect our study arouse more systematic approaches to financial market dynamics.
In the first part, we propose an econometric measure, terms as modularity, for characterizing the cluster structure of the daily price-returns of a universe of stocks. We conduct cluster analysis to establish the modularity measure. A high level of modularity implies that the cluster structure of the universe of stocks is highly evident, and low modularity implies blurred cluster structure. The modularity measure is shown to be related to the cycle of the economy. In addition, individual stock's sensitivity to the measure is shown to be related to its expected return. From 1992 to 2011, the average return of stocks with the lowest sensitivity exceeds that of the stocks with highest sensitivities by approximately 7.6\%. The consideration of modularity as an asset pricing factor expands the investment opportunity set to passive investors.
In the second part, we focus on analyzing the effect of the hidden demands/supplies in the high-frequency trading of a stock on its price dynamics. We propose a statistical estimation model for estimating hidden liquidity based on the limit orderbook data. Not only the estimated hidden liquidity can explain the market properties such as orderbook pressure better, the estimated hidden liquidity also refines the existing price impact model and achieves higher explanation power. The enhanced price impact model can serve as a foundation for devising optimal order execution strategies. The significance of our price impact model is tested by a simulated stock trading model. Tested on 62 trading days, our strategy yield significant transaction cost savings over benchmark methods.
]]>Reception: 3:30 p.m., 2nd floor atrium of ISyE Main.
Lecture: 4:00 p.m., Executive Education Room 228.
Lecture Title: Lessons Learned on Hard Work, Thinking Ahead, and Just Showing Up
Lecture Abstract: There is no such thing as an overnight success. Like the actor who does ten years of dinner theater before making it big, most of today’s leaders undergo significant challenges on the road to success. However, applying those insights can lead to significant growth. Join John Marshall, Senior Vice President and General Manager of AirWatch by VMware, as he shares how his experiences at Georgia Tech helped him take AirWatch from an apartment startup to a billion dollar buyout.
About John Marshall: John Marshall started AirWatch in 2003 running Cat-5 cable behind grease vats at local coffee shops for Wi-Fi HotSpots. After the iPhone emerged, he shifted the company’s focus to help organizations manage mobile devices for business use. With that pivot, the company grew from 150 to 1,900 employees in 4 years with 13,000 customers in 150 countries. In 2013, Marshall secured the largest Series A funding round of any software company in recent history at $200 million in 2013 and a year later he led the company’s acquisition by VMware for $1.54 billion. Ernst & Young named Marshall Entrepreneur of the Year 2013 for Technology.
]]>Join Dr. Maria Rey for an interactive one-hour webinar on "Measuring and Managing Performance in Supply Chain and Logistics Operations." Dr. Maria Rey is a renowned expert in the field of supply chain performance management and instructor.
After attending this webinar, attendees will receive a promo code for a discount towards the Measuring and Managing Performance in Supply Chain and Logistics Operations course being taught in Atlanta, GA, November 5-7, 2014!
Learn more about the GTSCL Certificate Series at http://www.scl.gatech.edu/certificates.
]]>Title: Optimality gap of constant-order policies decays exponentially in the lead time for lost sales models
Speaker: Linwei Xin
Abstract:
Inventory models with lost sales and large lead times have traditionally been considered intractable, due to the curse of dimensionality which arises from having to track the set of orders placed but not yet received (i.e. pipeline vector). Recently, Goldberg et al. (2012) laid the foundations for a new approach to solving these models, by proving that as the lead time grows large (with the other problem parameters fixed), a simple constant-order policy (proposed earlier by Reiman (2004)) is asymptotically optimal. This was quite surprising, as it is exactly this setting (i.e. large lead times) that was previously believed intractable. However, the bounds proven there are impractical, requiring the lead time to be very large before the constant-order policy becomes nearly optimal, e.g. requiring a lead time which is Omega(epsilon^{-2}) to ensure a (1+epsilon)-approximation guarantee, and involving a massive prefactor. The authors note that numerical experiments of Zipkin (2008) suggest that the constant-order policy performs quite well even for small lead times, and pose closing this gap (thus making the results practical) as an open problem.
In this work, we make significant progress towards resolving this open problem and closing this gap. In particular, for the infinite-horizon variant of the finite-horizon problem considered by Goldberg et al. (2012), we prove that the optimality gap of the same constant-order policy actually converges exponentially fast to zero, i.e. we prove that a lead time which is O(log(epsilon^{-1})) suffices to ensure a (1+epsilon)-approximation guarantee. We demonstrate that the corresponding rate of exponential decay is at least as fast as the exponential rate of convergence of the expected waiting time in a related single-server queue to its steady-state value. We also derive simple and explicit bounds for the optimality gap. For the special case of exponentially distributed demand, we further compute all expressions appearing in our bound in closed form, and numerically evaluate them, demonstrating good performance for a wide range of parameter values. Our main proof technique combines convexity arguments with ideas from queueing theory.
This is joint work with David A. Goldberg.
Sherwin and Kristy are two Ph.D. students from Carnegie Mellon University, currently visiting Georgia Tech to do research with Jim Xu in the College of Computing. Sherwin is a fifth year operations management student (at the Tepper School of Business) co-advised by Mor Harchol-Balter and Mustafa Akan, and Kristy is a third year computer science student advised by Mor Harchol-Balter. Their research involves a variety of scheduling and queueing problems (Markov chains, resource allocation, strategic and/or flexible customers/servers, etc.), with applications to problems in OR and CS. In this talk, first Sherwin, and then Kristy, will be giving back-to-back talks describing some of their recent research.
]]>SPEAKER: Brian Dandurand
ABSTRACT:
The needs of distributed solution approaches to decomposable nonconvex multiobjective optimization problems motivate the study of augmented Lagrangian coordination (ALC) methods and Gauss-Seidel methods from single objective optimization. The application of certain scalarization techniques to a nonconvex, vector-valued objective function results in a reformulated single objective problem (RSOP) whose objective function may not preserve certain properties assumed in Gauss-Seidel approaches such as the alternating direction method of multipliers (ADMM). The block coordinate descent method (BCD) is considered as an alternative distributed optimization approach. While BCD requires that the constraints possess a certain decomposable structure, the formulation of the RSOP as a decomposable problem may require the introduction of extra variables and extra nondecomposable constraints. Thus, an ALC approach such as the method of multipliers must be integrated with BCD, and a corresponding analysis of such an integrated approach is warranted.
In this presentation, a brief introduction to these concepts will be provided. Then state-of-art results for BCD and ALC methods are provided and compared with those for ADMM. A BCD coordination (BCDCoor) method consisting of an integration of BCD and ALC methods is stated as an alternative to ADMM for solving nonconvex RSOPs with nonseparable objective functions. A convergence analysis of solution-multiplier pair sequences generated by BCDCoor requires certain extensions to the state-of-art results for BCD and ALC methods. These required extensions are described, and current contributions to this end are discussed briefly.
SPEAKER: Ganesh Janakiraman
ABSTRACT:
We study a model of a firm managing its inventory of a single product by sourcing supplies from two supply sources, a regular supplier who offers a lower unit cost and a longer lead time than a second, emergency, supplier. A practically implementable policy for such a firm is a Tailored Base-Surge (TBS) Policy (Allon and Van Mieghem, 2010) to manage its inventory: Under this policy, the firm procures a constant quantity from the regular supplier in every period and dynamically makes procurement decisions for the emergency supplier. Allon and Van Mieghem describe this practice as using the regular supplier to meet a base level of demand and the emergency supplier to manage demand surges, and they conjecture that this practice is most effective when the lead time difference between the two suppliers is large. We confirm these statements in two ways. First, we show the following analytical result: When demand is composed of a base demand random component plus a surge demand random component, which occurs with a certain small probability, the best TBS Policy is close to optimal (over all policies) in a well defined sense. Second, we also numerically investigate the cost-effectiveness of the best TBS policy on a test bed of problem instances. The emphasis of this investigation is the study of the effect of the lead time difference between the two suppliers. Our study reveals that the cost difference between the best TBS policy and the optimal policy decreases dramatically as the lead time of the regular supplier increases. On our test bed, this cost difference decreases from an average (over the test bed) of 21 % when the lead time from the regular supplier is two periods (the emergency supplier offers instant delivery) to 3.5 % when that lead time is seven periods.
]]>SPEAKER: Chris Ryan
ABSTRACT:
We explore how Fourier-Motzkin elimination, a standard tool infinite dimensional linear programming, can be used to understand the duality theory of more general optimization problems, including semi-infinite linear programming, convex, and conic programming.
This is joint work with Amitabh Basu (Johns Hopkins) and Kipp Martin (University of Chicago).
Short Biography:
Chris is currently an assistant professor in operations management at the University of Chicago Booth School of Business. He has two major research interests. The first is in optimization theory, including infinite dimensional optimization, bilevel optimization, discrete optimization, and computational game theory.SPEAKER: Irina Dolinskaya
ABSTRACT:
Planning a trip with an electric vehicle requires consideration of both battery dynamics and the availability of charging infrastructure. Recharging costs for an electric vehicle, which increase as the battery's charge level increases, are fundamentally different than refueling costs for conventional vehicles, which do not depend on the amount of fuel already in the tank. Furthermore, the viability of any given route is sensitive to the availability of charging stations along the way. In this work, we study the problem of finding an optimal routing and recharging policy for an electric vehicle in a grid network. We develop and analyze a variety of models depending on the amount and timing of information available to the EV driver while traveling. A numerical study demonstrates the performance and solution quality of our algorithms using simulated urban charging infrastructure networks.
BIO:
Irina Dolinskaya is an assistant professor of Industrial Engineering and Management Sciences and William A. Patterson Junior Chair in Transportation at Northwestern University. She obtained M.S. and Ph.D. degrees in Industrial and Operations Engineering from the University of Michigan, and B.S. degree in Industrial Engineering from the University of Florida.
Her research interests include operations research with emphasis on large scale and computationally demanding dynamic programming problems, optimal path finding in evolving systems using real-time information, and effective planning under limited information. Applications include problems in humanitarian logistics, optimum vessel performance in evolving nonlinear wavefields, electric vehicle routing, and autonomous navigation for amphibious vehicles.
Dr. Dolinskaya is the winner of the INFORMS Transportation Science & Logistics Society Dissertation Prize. She is also the 2008 recipient of the Bonder Scholarship for Applied Operations Research in Military Applications. Dr. Dolinskaya is actively involved in various leadership and mentorship roles. Her academic achievements and contribution to the university community has been recognized by awarding her the University of Michigan College of Engineering Distinguished Leadership Award in 2008 and Distinguished Achievement Award in 2009.
]]>
Please RSVP online for any of the below activities at http://www.scl.gatech.edu/gtscnko.
GTSCN and the Supply Chain & Logistics Institute will host an Open House at SCL's suite in the ISyE complex (Groseclose Building, 2nd floor, Suite 228). All interested parties are invited to stop by, mix and mingle; hear the latest on what is going on in research, professional education, degree programs, forums, etc. in Supply Chain at Georgia Tech.
Unfamiliar with the GT campus? We will be offering one-hour campus tours at 11am and 1pm, led by a GT student.
The Georgia Tech Supply Chain Network will have a tent set up on the Tech Green Tailgating Area, just northeast of the Student Center. Snacks and drinks will be available. This activity will take place on November 1 and begin 4 hours prior to game time.
Stay tuned for other organizational and activity notices and if you haven’t done so already, please add your name to the mailing list at http://www.scl.gatech.edu/sclaffinity to be notified of future events.
]]>
SPEAKER: Aleksandra Sesa Slavkovic
ABSTRACT:
Increasing volumes of personal and sensitive data are collected and archived by health networks, government agencies, search engines, social networking websites, and other organizations. The social networks are a prominent source of data for researchers in economics, epidemiology and sociology and have sparked a flurry of research in statistical methodology for network analysis. While the social benefits of analyzing these data are significant, their release can be devastating to the privacy of individuals and organizations. In this talk, we give a brief overview of challenges associated with protecting confidential data, and the problem of releasing summary statistics of graphs needed to build statistical models for networks while preserving privacy of individual relations. Our goal is to ensure that a user is able to perform standard statistical inference with the released data while satisfying a rigorous definition of privacy risk. We present an algorithm for releasing degree sequences of undirected graphs under the framework of differential privacy. The algorithm is designed to provide utility for inference in random graph models whose sufficient statistics are functions of degree sequences. Specifically, we focus on the tasks of existence of maximum likelihood estimates, parameter estimation and goodness-of-fit testing for the beta model of random graphs. We show the usefulness of our algorithm by evaluating it empirically on simulated and real-life datasets. As the released degree sequence is graphical, our algorithm can also be used to release synthetic graphs under the beta model. Time permitting, we will discuss extensions to more general exponential random graph models (ERGMs). (This is joint work with Vishesh Karwa)
]]>SPEAKER: Alex Shapiro
ABSTRACT:
In many practical situations one has to make decisions sequentially based on data available at the time of the decision and facing uncertainty of the future. This leads to optimization problems which can be formulated in a framework of multistage stochastic optimization. In this talk we consider risk neutral and risk averse approaches to multistage stochastic programming. We discuss conceptual and computational issues involved in formulation and solving such problems. As an example we give numerical results based on the Stochastic Dual Dynamic Programming method applied to planning of the Brazilian interconnected power system.
SPEAKER: Mark Davenport
ABSTRACT:
In this talk I will focus on the problem of recovering a sparse vector from a small number of noisy measurements. To begin, I will consider the case where the measurements are acquired in a nonadaptive fashion. I will establish a lower bound on the minimax mean-squared error of the recovered vector which very nearly matches the performance of â„“1-minimization techniques, and hence shows that these techniques are essentially optimal. I will then consider the case where the measurements are acquired sequentially in an adaptive manner. I will prove a lower bound that shows that, surprisingly, adaptivity does not allow for substantial improvement over standard nonadaptive techniques in terms of the minimax MSE. Nonetheless, I will also show that there are important regimes where the benefits of adaptive sensing are clear and overwhelming.
]]>SPEAKER: Miguel Anjos
ABSTRACT:
A smart grid is the combination of a traditional power distribution system with two-way communication between suppliers and consumers. This combination is expected to deliver energy savings, cost reductions, and increased reliability and security, but smart grids introduce numerous challenges for the management of the resulting system. These include integrating renewable energy sources such as wind and solar electricity generation, managing bidirectional flows of power, and incorporating demand-response. We will present an overview of the challenges in this area, examples of how optimization is helping to meet these challenges, and important directions for future research.
Bio:
Miguel F. Anjos is Full Professor and Canada Research Chair in the Department of Mathematics & Industrial Engineering of Polytechnique Montreal, and is the Founding Director of Polytechnique’s Trottier Institute for Energy. He received his degrees from McGill University, Stanford University, and the University of Waterloo. He is Editor-in-Chief of Optimization and Engineering and serves on the editorial boards of several other journals. He recently completed a 3-year term as Program Director for the SIAM Activity Group on Optimization, and currently serves on the Council of the Mathematical Optimization Society. He is also a member of the Research Review Committee of Mitacs. He received the Méritas Teaching Award from Polytechnique in 2012. He was awarded a Humboldt Research Fellowship for Experienced Researchers in 2009, and the Queen Elizabeth II Diamond Jubilee Medal for significant contributions to mathematical optimization and its industrial applications.
Where: ISyE Main Bldg, Executive Classroom (Room 228) and ISyE Atrium
When: Tuesday, November 18, 11:00AM-2:00PM
What: The session will include:
Please plan on staying for the duration of the event and bring copies of your resume and business cards. Dress is business casual.
The event is sponsored through the generosity and support of APICS - Atlanta Chapter. APICS is a non-profit educational organization addressing operations management and supply chain management issues, and providing professional development opportunities to our members. Visit http://www.apicsatlanta.org/ to learn more and make sure to stop by the APICS table at the event.
]]>SPEAKER: Dr. Pascal Van Hentenryck (Australian National University, Canberra, ACT, Australia)
ABSTRACT:
The design, control, and operation of the power grid, probably the largest and most expansive system ever engineered, require the solving of optimization problems over the steady-state power flow equations. The resulting mixed nonconvex programs are often computationally challenging and increasingly so with the increased stochasticity in generation and load. This talk presents some new complexity results, as well as a number of advances in approximating and relaxing the power flow equations to address emerging applications in power systems, including large-scale power restoration after blackouts, the design of resilient networks, and the integration of renewable generation. Extensive computational results demonstrate some of the benefits of the proposed techniques.
]]>jennifer.harris@isye.gatech.edu
]]>Professionals and students, please join the APICS Atlanta Chapter for one of its monthly professional dinner meetings (PDM), Tuesday, Nov 18th 5:30-8pm. Network with professionals and listen to an inspiring speech. This is a fantastic opportunity to expand your network, gain insights about the industry, and potentially find your passion.
Presenter: Deb Hansford
Title: Owner of PreCrest, LLC
APICS Certification: CFPIM, CIRM, CSCP, C.P.M., CPSM
Abstract: Professionals of various experience levels typically seek to improve their career and provide value to their company. Many people focus on the "what" such as reducing costs with suppliers or improving processes. Then they consider "how" to design and implement the changes.
This presentation uses a specific Ted Talk as the foundation to reiterate the importance and significance of "why" and uses the Golden Circle to illustrate the shift in our thought processes.
During this interactive session, teams will learn and apply the power of "why". Hope you join us for this lively event that will help you think differently and hopefully boost your success both at home and at work.
Brief Bio: People want to learn in fun environments and Deb delivers! She uses her practical experience in supply chain to help illustrate concepts along with simulations and games. Some people see "outside the box" for creative ideas, but Deb has been accused of not seeing the box. Based on participant surveys, she takes that as a compliment. She is the owner of PreCrest, LLC since 2004 and encourages professionals and companies to "Learn More, Do More, Earn More".
]]>SPEAKER: Monica Villarreal
ADVISER: Dr. Pinar Keskinocak
SUMMARY:
The healthcare expenditure in the United States reached $3.8 trillion dollars in 2013, and it is projected that it will continue to outpace the rest of the economy. There are strong incentives to improve the efficiency of the healthcare system through a better planning and management of resources.
In this thesis we address three capacity planning problems motivated by healthcare applications. In the first application, we develop, implement, and assess the impact of analytical models, accompanied by a decision-support tool, for operating room (OR) staff planning decisions with different service lines. First, we propose a methodology to forecast the staff demand by service line. We use these results in a 2-phase mathematical model that defines the staffing budget for each service line, and then decides how many staff to assign to each potential shift and day pair; while considering staff overtime and pooling policies and other staff planning constraints. We also propose a heuristic to solve the model's second phase. We implement these models using historical data from a community hospital and analyze the effect of different model parameters and settings. Compared with the current practice, we reduce delays and staff pooling at no additional cost. We validate these conclusions through a simulation model.
In the second application, we consider the problem of staff planning and scheduling when there is an accepted time window between orders arrival and fulfillment, with the goal of obtaining a balanced schedule that focuses on on-time demand fulfillment but also considers staff characteristics and operative practices. This means that solving this problem requires simultaneously scheduling the staff and the forecasted demand. We propose, implement, and analyze the results of a model for staff and demand scheduling under this setting, accompanied by a decision tool. We implement this model in a company that offers document processing and other back-office services to healthcare providers. We provide details on the model validation, implementation, and results, including an increase of the company's staff productivity in about 25%. We also provide insights on the effects of some of the model's parameters and settings, and assess the performance of a proposed heuristic to solve this problem.
In the third application, we consider a non-consumable resource planning problem. Demand consists of a set of jobs. Each job has a scheduled start time and duration, and corresponds to a particular demand class that requires a subset of resources. Jobs can be `accepted' or `rejected', and the service level is measured by the acceptance of jobs. The goal is to find the capacity level that minimizes the total cost of the resources, subject to service level constraints, globally and by demand class. We first analyze the complexity of this problem under different special cases, and then we propose a model to find the optimal inventory for each type of resource. We show the convergence of the sample average approximation method to solve a stochastic extension of the model. This problem is motivated by the inventory planning of surgical instruments for ORs. We study the effects of different model parameters and settings on the cost and service levels, based on surgical data from a community hospital.
SPEAKER: Mark Squillante
ABSTRACT:
We consider an integrated suite of mathematical models and methods that supports the effective and efficient management and planning of human capital supply chains by addressing distinct features and characteristics of human talent and skills which cannot be handled via traditional supply chain management. This consists of solutions for (1) statistical forecasting of future demand and human-talent requirements, (2) risk-based stochastic human-talent capacity planning, (3) stochastic modeling and optimization/control of human-talent supply evolutionary dynamics over time, (4) optimal multiskill supply-demand matching, and (5) stochastic optimization of business decisions and investments to manage human-talent shortages and overages. These solutions include contributions in the areas of stochastic models and stochastic optimization/control. The suite of models and methods constitutes an end-to-end framework that has been deployed as an important part of a human talent management and planning process within IBM.
]]>SPEAKER: Chris Schmid
ABSTRACT:
Comparative effectiveness usually involves evaluation of multiple interventions and may involve multiple outcomes measured at multiple times as well. Meta-analysis, whether of continuous or discrete outcomes, has in the past focused on summarizing the evidence comparing two treatments or classes of treatments. Recently, methods have been developed to integrate comparisons of multiple treatments into coherent models that allow simultaneous comparison of all treatments, combining the direct evidence from head-to-head studies with indirect evidence from trials that involve common comparators.
The network models provide estimates of the relative effectiveness or harms of all included treatments, and a ranking with associated probability estimates. These methods depend on a crucial assumption that the direct and indirect evidence are compatible (consistency) and that treatments are mutually exchangeable across studies (transitivity). This talk will introduce meta-analysis in the context of evidence-based science and will then outline the basic principles of network meta-analysis and assessment of the validity of its assumptions including the key role that potential effect modifiers play. Examples of its application to different types of outcomes, both efficacy and safety with discussion of incomplete data problems will be discussed.
This workshop will improve presentation skills for graduate students about to give job talks
RSVP at:
http://www.isye.gatech.edu/apps/RSVP/job-talk-workshop/
]]>SPEAKER: Kris Johnson
ABSTRACT:
This talk highlights two projects in a stream of work that uses data-driven approaches to develop effective revenue management strategies for online retailers.
In the first project, we partner with the online flash sales retailer Rue La La to develop and implement a pricing decision support tool that sets initial prices for new products. To do this, we use machine learning techniques to predict future demand and develop an algorithm to efficiently solve the subsequent multi-product price optimization. We show results from a five-month long field experiment that we designed and conducted to test the impact of our tool’s recommended price increases on demand, and we estimate an associated impact on revenue of approximately 10%. This is joint work with David Simchi-Levi and Alex Lee and was awarded the 2014 INFORMS Revenue Management and Pricing Section Practice Award.
Motivated by our work with Rue La La, our second project considers the dynamic pricing problem of an online retailer facing limited inventory and unknown demand. The multi-armed bandit problem has been a well-studied formulation of the dynamic pricing problem given unlimited inventory of a product. We have incorporated limited inventory constraints into a common algorithm for the multi-armed bandit problem, and we show that our algorithm has strong empirical and theoretical performance results. This is joint work with David Simchi-Levi and He Wang.
]]>
The visit will have no specific agenda and Dean May will not make a presentation nor have
any prepared remarks. This is an opportunity for the faculty and staff to ask questions,
share concerns, or offer suggestions to the Dean. You may come in one at a time or as
small group but the intent is to have people coming and going throughout the hour.
At this meeting Associate Dean Larry Jacobs and Associate Chair Chen Zhou will be leading us in preparations for our upcoming ABET accreditation visit scheduled for September 21 – 23.
During the meeting you will get a good overview of what will be happening during the visit. A key thing you will learn is, among other things, the questions – and answers to the questions – that our ABET program evaluator will be asking individual faculty members on September 22.
You will also learn where we think our BSIE program compliance is strong, and what parts are a worry. Most of all, you will get up to speed on what you will be doing during the ABET visit, and how to do it well – a key role in our success.
Our special thanks go out to Chen Zhou for his leadership of our BSIE ABET preparations, and to members of his self-study preparation team, including Dima Nazzal and Brandy Blake. We also appreciate the leadership and help provided by Larry Jacobs and Terri Lee in the Dean’s office, and the collaborations from ABET leaders in other CoE units.
]]>The efficient flow of inbound materials through your supply chain can have a significant impact on cost, quality, service, and delivery to your customer. With continued pressures from globalization, market volatility, and innovation expectations, companies are extending their reliance on lean principles to outside the four walls of the manufacturing facility.
Lean inbound logistics requires strategic coordination to synchronize suppliers, transportation providers and multiple supply chain partners. And like all complex multi-party operations, the road to improvement will have its challenges. Such hurdles could include balancing inventory cost with transportation cost, the lack of leadership understanding and support, and the realities of incumbent manufacturing and procurement contracts and systems.
This course focuses on the why and how to implement lean logistics to support the lean supply chain operations – both in manufacturing and distribution. Areas of focus include: lean strategy development, identifying and overcoming operational realities, and learning the tools necessary for successful implementation.
Upon completion of this course, you will be able to:
Participants receive a course notebook and the Building a Lean Fulfillment Streamworkbook
None.
Brad Bossence is the Vice President of Customer Relations for LeanCor Supply Chain Group.
Founded in 2005, LeanCor is a trusted supply chain partner that delivers operational improvement and measurable financial results. Unlike other third party logistics providers, LeanCor offers a unique combination of third party logistics services, hands-on consulting, and training and education.
Brad has over 14 years of third party logistics experience with a specific focus in Japanese production system environments such as Toyota USA, Toyota Canada, Toyota Europe, Kubota, Yamaha, Suzuki, and Subaru. His previous roles include General Manager of Logistics and Operations at Transfreight as well as various contract and operations management positions across the globe.
As the Vice President of Customer Relations, Brad’s responsibilities have included the vision, leadership and momentum necessary for LeanCor to develop and significantly grow its global customer base. In addition, he has led on a variety of extensive customer projects – most recently with Cummins Inc. in San Luis Potosi, Mexico on a Materials Flow Redesign and Warehouse Relocation. LeanCor is committed to continuous improvement and fully recognizes performance is measured by real results. As an operator and thought leader, LeanCor relentlessly tries to optimize those processes that add value and eliminate those that are waste.
Brad holds a Bachelor of Commerce and an MBA with a focus in International Business and Organizational Behavior from the University of Windsor. He is a certified Professional in Human Resources (PHR), and holds various lean and six sigma accreditations.
Brad resides in Newnan, Georgia with his wife Aubre and their son Townes.
This course counts towards the Supply Chain & Logistics Certificate.
On the first day, please check in at least 30 minutes before the class start time.
Supply chain management and logistics encompasses all the activities involved in getting products to consumers including planning, storing, moving, and accounting for inventory. Inventory availability is the most important aspect of customer service, and the cost of inventory is one of the most important entries on a company's balance sheet.
Recognition of the balance sheet implications of inventory in supply chain management has launched a variety of industry-wide inventory reduction initiatives. Despite all these initiatives to reduce inventory in the supply chain, inventory levels for most companies have remained the same or increased. This course is focused on understanding how to efficiently provide the level of inventory that is really necessary for customer service while minimizing the inventory resulting from poor supply chain management.
Participants receive a course notebook.
None.
Daniel L. Gardner is founder and president of Trade Facilitators, Inc., a Los Angeles based supply chain consulting and training firm. Prior to founding TFI, Mr. Gardner spent 23 years in the Third Party Logistics business where he held senior management positions with entities that include Exel Global Logistics and DHL Global Forwarding.
Relief requirements for public health and humanitarian events are in general both unknown in size and type, and are affected by dynamic and hard to measure factors such as geographic location, local economy, infrastructure, social and political conditions, etc. Preparing for long-term development and response to emergent events often involves uncertainty in timing, scope, or scale. Pre-planning for these situations requires an understanding of forecasting, distribution network design, and strategies for managing the uncertainty. This course will examine methods and models for making pre-planning decisions and explore the significant value that is obtained through informed decision-making in advance of an unpredictable event.
Pre-Course Activities (2.5 hrs) - Online via MoodleRooms
Classroom Activities (2 days) - Georgia Tech Global Learning Center
Post-Course Activities (5 hrs) - Online via MoodleRooms
NOTE: Pre-course and post-course activities will conducted online using the MoodleRooms online learning management system. Access instructions will be provided to registrants when details become available.
Pre-Course Activities - Conducted online via MoodleRooms
Distribution Network Design – 1 hour
Forecasting – 1.5 hours
Classroom Activities
Day 1
Day 2
Post-Course Activities - Conducted online via MoodleRooms
Participants receive readings, case studies, spreadsheet files, and lecture slides, and will be given access to the pre- and post-course web-based activities.
Students need a laptop with Microsoft Excel and the ability to connect to a high-speed internet connection (internet access is provided for onsite portions of course).
None.
Dr. Swann is the Harold R. and Mary Anne Nash Associate Professor in the School of Industrial and Systems Engineering. She is currently focused on the modeling and analysis of problems and algorithms in logistics, transportation and supply chain management. She has particular interests in developing and analyzing tools to manage demand, such as pricing, revenue management, or lead-time quotation, to increase the flexibility in the system and is currently doing work in humanitarian supply chains. Other research interests include applications of economics and optimization to healthcare policy.
She was awarded an NSF CAREER grant in 2004, and recently, one of her papers was selected as a Finalist in the Shepherd award at the CDC. In 2002, she received the Doctoral Dissertation Award from the Council of Logistics Management and was a Finalist in the Dantzig Doctoral Dissertation Competition at INFORMS. In 2006 she was inducted into the Council of Outstanding Young Engineering Alumni of Georgia Tech.
Dr. Özlem Ergun is the Coca Cola Associate Professor in the School of Industrial and Systems Engineering. She holds a Ph.D. in Operations Research from the Massachusetts Institute of Technology. Professor Ergun's research focuses on the design and management of large-scale networks. Specifically, she studies logistics and communications networks that are dynamic, partially decentralized, and are used and operated by coordinating but selfish entities. Her main research contributions are the development of a set of new algorithmic and analytical tools and their applications to important real world problems. She is also a co-founder and co-director of the The Center for Health and Humanitarian Logistics at the Supply Chain and Logistics Institute. She teaches undergraduate and graduate courses in optimization and logistics. Dr. Ergun was awarded the NSF Career Award in 2003.
Pinar Keskinocak is the Joseph C. Mello Professor in the School of Industrial and Systems Engineering, Associate Director of Research for the Health Systems Institute, and the co-director of the Center for Health and Humanitarian Logistics at Georgia Institute of Technology. She received B.S. and M.S. degrees in industrial engineering from Bilkent University in Ankara, Turkey, and a Ph.D. in operations research from Carnegie Mellon University.
Dr. Keskinocak's research focuses on supply chain management, with an emphasis on resource allocation, revenue management, auctions/pricing, due date/lead-time decisions, production planning/scheduling, and logistics/transportation. She is also actively engaged in research and applications in healthcare and humanitarian logistics.
Dr. Keskinocak is an associate editor of Management Science and IIE Transactions, a senior editor of Production and Operations Management (POMS), and on the editorial board of Journal of Revenue & Pricing Management. She is one of the founding members of the INFORMS-JFIG (Junior Faculty at Informs) group and has served as the president of JFIG.
]]>Numerous tactical decisions must be made in the response to a public health or humanitarian event. Many of these decisions are concerned with the timely and efficient procurement, allocation, and distribution of resources (e.g. funds, supplies, volunteers) through a supply chain. This course will explore methodologies for tactical decision making including procurement and inventory policies, strategies for distribution and allocation of limited resources, and transportation decisions.
Pre-Course Activities (4.5 hrs) - Online via MoodleRooms
Classroom Activities (2.5 days) - Georgia Tech Global Learning Center
Post-Course Activities (3.5 hrs) - Online via MoodleRooms
NOTE: Pre-course and post-course activities will conducted online using the MoodleRooms online learning management system. Access instructions will be provided to registrants when details become available.
Pre-Course Activities - Conducted online via MoodleRooms
Classroom Activities
Day 1
Day 2
Day 3
Post-Course Activities - Conducted online via MoodleRooms
Participants receive readings, case studies, spreadsheet files, and lecture slides, and will be given access to the pre- and post-course web-based activities.
Students need a laptop with Microsoft Excel and the ability to connect to a high-speed internet connection (internet access is provided for onsite portions of course).
None.
Dr. Swann is the Harold R. and Mary Anne Nash Associate Professor in the School of Industrial and Systems Engineering. She is currently focused on the modeling and analysis of problems and algorithms in logistics, transportation and supply chain management. She has particular interests in developing and analyzing tools to manage demand, such as pricing, revenue management, or lead-time quotation, to increase the flexibility in the system and is currently doing work in humanitarian supply chains. Other research interests include applications of economics and optimization to healthcare policy.
She was awarded an NSF CAREER grant in 2004, and recently, one of her papers was selected as a Finalist in the Shepherd award at the CDC. In 2002, she received the Doctoral Dissertation Award from the Council of Logistics Management and was a Finalist in the Dantzig Doctoral Dissertation Competition at INFORMS. In 2006 she was inducted into the Council of Outstanding Young Engineering Alumni of Georgia Tech.
Dr. Özlem Ergun is the Coca Cola Associate Professor in the School of Industrial and Systems Engineering. She holds a Ph.D. in Operations Research from the Massachusetts Institute of Technology. Professor Ergun's research focuses on the design and management of large-scale networks. Specifically, she studies logistics and communications networks that are dynamic, partially decentralized, and are used and operated by coordinating but selfish entities. Her main research contributions are the development of a set of new algorithmic and analytical tools and their applications to important real world problems. She is also a co-founder and co-director of the The Center for Health and Humanitarian Logistics at the Supply Chain and Logistics Institute. She teaches undergraduate and graduate courses in optimization and logistics. Dr. Ergun was awarded the NSF Career Award in 2003.
Pinar Keskinocak is the Joseph C. Mello Professor in the School of Industrial and Systems Engineering, Associate Director of Research for the Health Systems Institute, and the co-director of the Center for Health and Humanitarian Logistics at Georgia Institute of Technology. She received B.S. and M.S. degrees in industrial engineering from Bilkent University in Ankara, Turkey, and a Ph.D. in operations research from Carnegie Mellon University.
Dr. Keskinocak's research focuses on supply chain management, with an emphasis on resource allocation, revenue management, auctions/pricing, due date/lead-time decisions, production planning/scheduling, and logistics/transportation. She is also actively engaged in research and applications in healthcare and humanitarian logistics.
Dr. Keskinocak is an associate editor of Management Science and IIE Transactions, a senior editor of Production and Operations Management (POMS), and on the editorial board of Journal of Revenue & Pricing Management. She is one of the founding members of the INFORMS-JFIG (Junior Faculty at Informs) group and has served as the president of JFIG.
]]>
Despite having common goals, often the lack of cooperation and coordination between humanitarian organizations results in procurement and allocation inefficiencies. As a result, a systems view of a humanitarian effort is needed to ensure appropriate use of scarce resources to meet the goals at hand. This course will focus on conceptual and modeling skills to understand and effectively manage humanitarian response from a systems perspective. Models will address system characteristics (e.g. demand dependencies) that drive system dynamics and policies to regulate performance. Course topics include methods for improving coordination and collaboration, addressing demand dependencies, and reliably measuring and evaluating system performance.
Pre-Course Activities (6 hrs) - Online via MoodleRooms
Classroom Activities (2.5 days) - Georgia Tech Global Learning Center
Post-Course Activities (4 hrs) - Online via MoodleRooms
NOTE: Pre-course and post-course activities will conducted online using the MoodleRooms online learning management system. Access instructions will be provided to registrants when details become available.
Pre-Course Activities - Conducted online via MoodleRooms
Classroom Activities
Day 1
Day 2
Day 3
Post-Course Activities - Conducted online via MoodleRooms
Participants receive readings, case studies, spreadsheet files, and lecture slides, and will be given access to the pre- and post-course web-based activities.
Students need a laptop with Microsoft Excel and the ability to connect to a high-speed internet connection (internet access is provided for onsite portions of course).
None.
Dr. Swann is the Harold R. and Mary Anne Nash Associate Professor in the School of Industrial and Systems Engineering. She is currently focused on the modeling and analysis of problems and algorithms in logistics, transportation and supply chain management. She has particular interests in developing and analyzing tools to manage demand, such as pricing, revenue management, or lead-time quotation, to increase the flexibility in the system and is currently doing work in humanitarian supply chains. Other research interests include applications of economics and optimization to healthcare policy.
She was awarded an NSF CAREER grant in 2004, and recently, one of her papers was selected as a Finalist in the Shepherd award at the CDC. In 2002, she received the Doctoral Dissertation Award from the Council of Logistics Management and was a Finalist in the Dantzig Doctoral Dissertation Competition at INFORMS. In 2006 she was inducted into the Council of Outstanding Young Engineering Alumni of Georgia Tech.
Dr. Özlem Ergun is the Coca Cola Associate Professor in the School of Industrial and Systems Engineering. She holds a Ph.D. in Operations Research from the Massachusetts Institute of Technology. Professor Ergun's research focuses on the design and management of large-scale networks. Specifically, she studies logistics and communications networks that are dynamic, partially decentralized, and are used and operated by coordinating but selfish entities. Her main research contributions are the development of a set of new algorithmic and analytical tools and their applications to important real world problems. She is also a co-founder and co-director of the The Center for Health and Humanitarian Logistics at the Supply Chain and Logistics Institute. She teaches undergraduate and graduate courses in optimization and logistics. Dr. Ergun was awarded the NSF Career Award in 2003.
Pinar Keskinocak is the Joseph C. Mello Professor in the School of Industrial and Systems Engineering, Associate Director of Research for the Health Systems Institute, and the co-director of the Center for Health and Humanitarian Logistics at Georgia Institute of Technology. She received B.S. and M.S. degrees in industrial engineering from Bilkent University in Ankara, Turkey, and a Ph.D. in operations research from Carnegie Mellon University.
Dr. Keskinocak's research focuses on supply chain management, with an emphasis on resource allocation, revenue management, auctions/pricing, due date/lead-time decisions, production planning/scheduling, and logistics/transportation. She is also actively engaged in research and applications in healthcare and humanitarian logistics.
Dr. Keskinocak is an associate editor of Management Science and IIE Transactions, a senior editor of Production and Operations Management (POMS), and on the editorial board of Journal of Revenue & Pricing Management. She is one of the founding members of the INFORMS-JFIG (Junior Faculty at Informs) group and has served as the president of JFIG.
]]>Transforming an organization from traditional thinking to lean thinking requires leadership. This is the third course in a 3-course series on becoming a Lean Supply Chain professional. While the previous courses focus on strategic and tactical implementation of the lean supply chain, this final course "builds" the individual into a lean leader. This transformation is critical to navigate through the waters of change management that is required to successfully execute and sustain the lean supply chain journey.
In the third course participants will complete a deep dive of the concept of House of Lean and explore the main aspects of lean leadership. Among other important topics, participants will learn "go see" management, "A3 thinking" and "leader-as-teacher" concepts.
Day 1 - The Lean Culture
Day 2 - Lean Principles Deep Dive
Day 3 - The Lean Leader
Robert Martichenko is CEO of LeanCor, LLC. He has years of supply chain, logistics and Lean implementation experience. This experience includes multiple Lean Supply Chain implementations supporting successful organizations including Toyota Motor Manufacturing. Robert authored the books "Success in 60 Seconds" and "Everything I know about Lean I Learned in First Grade." He also co-authored the logistics management book "Lean Six Sigma Logistics," published by J. Ross Publishing and co-authored the workbook "Building the Lean Fulfillment Stream," published by the Lean Enterprise Institute. Robert complements his professional experience with a Bachelor Degree in Mathematics from the University of Windsor, an MBA in Finance from Baker College and is a trained Six Sigma Black Belt. He can be reached at RMartichenko@leancor.com.
Brad Bossence is the Vice President of Customer Relations for LeanCor Supply Chain Group.
Founded in 2005, LeanCor is a trusted supply chain partner that delivers operational improvement and measurable financial results. Unlike other third party logistics providers, LeanCor offers a unique combination of third party logistics services, hands-on consulting, and training and education.
Brad has over 14 years of third party logistics experience with a specific focus in Japanese production system environments such as Toyota USA, Toyota Canada, Toyota Europe, Kubota, Yamaha, Suzuki, and Subaru. His previous roles include General Manager of Logistics and Operations at Transfreight as well as various contract and operations management positions across the globe.
As the Vice President of Customer Relations, Brad’s responsibilities have included the vision, leadership and momentum necessary for LeanCor to develop and significantly grow its global customer base. In addition, he has led on a variety of extensive customer projects – most recently with Cummins Inc. in San Luis Potosi, Mexico on a Materials Flow Redesign and Warehouse Relocation. LeanCor is committed to continuous improvement and fully recognizes performance is measured by real results. As an operator and thought leader, LeanCor relentlessly tries to optimize those processes that add value and eliminate those that are waste.
Brad holds a Bachelor of Commerce and an MBA with a focus in International Business and Organizational Behavior from the University of Windsor. He is a certified Professional in Human Resources (PHR), and holds various lean and six sigma accreditations.
Brad resides in Newnan, Georgia with his wife Aubre and their son Townes
]]>As supply chain executives become more instrumental in supporting long term strategic objectives for their firms, they need to complement traditional SC operational knowledge with a more strategic view of their role in delivering aligned results to the business. This course addresses this requirement by exposing and explaining to supply chain leaders different lenses of strategic planning applied to SCM and the specific implications on SC operations.
During the course, attendees will have several opportunities to assess their current supply chain strategy, formulate a new one, discuss about keys to implement a supply chain strategy, and how to review and align one.
For the duration of the course, participants will have the opportunity to play with an extended simulation game of a fictional company, and see the impact of supply chain strategic decisions in real time, while monitoring their ability to manage uncertainty and deliver financial results for the firm.
Participants receive a course notebook.
None.
Maria Rey-Marston successfully combines academic, consulting and applied research activiaties. Her research and consulting focus is on the design and use of performance management systems, both within intra-firm processes and for inter-firm relationships. Her academic and teaching activities are centered on supply chain strategy, outsourcing and inter-firm relationship management, and the strategic connection between supply chain and financial performance.
Since 2012, Maria is Chief Executive Officer of Periphery Labs, a Serenbe GA -based firm that specializes in service innovation and periphery management (networks of external business relationships). She is Senior Advisor with MRM+Partners, leading the Supply Chain Strategy practice of the firm. Her academic and teaching activity is conducted from the Supply Chain & Logistics Institute at Georgia Tech, where she has been affiliated since 1995.
To become a lean supply chain professional, you need to first become a lean thinker and lean problem solver. This is the first course in a 3-course series on becoming a Lean Supply Chain professional. Students will be introduced to lean thinking and critical lean concepts. In addition, students with become proficient problem solvers through gained skills of waste identification and use of fundamental problem solving tools to eliminate waste at the root cause.
This first course is a pivot point in the educational process, and this is where current mental models and business paradigms will be challenged. Participants will learn to see operations from a new vantage point. Upon arrival back to the workplace, participants will be able to "talk" the talk of lean and also have a keen eye for operational waste. However, the real test of the first course is when the participant can "walk" the lean walk and solve business problems at the root cause, completely eliminating the problem for the organization
Robert Martichenko is CEO of LeanCor, LLC. He has years of supply chain, logistics and Lean implementation experience. This experience includes multiple Lean Supply Chain implementations supporting successful organizations including Toyota Motor Manufacturing. Robert authored the books "Success in 60 Seconds" and "Everything I know about Lean I Learned in First Grade." He also co-authored the logistics management book "Lean Six Sigma Logistics," published by J. Ross Publishing and co-authored the workbook "Building the Lean Fulfillment Stream," published by the Lean Enterprise Institute. Robert complements his professional experience with a Bachelor Degree in Mathematics from the University of Windsor, an MBA in Finance from Baker College and is a trained Six Sigma Black Belt. He can be reached at RMartichenko@leancor.com.
Brad Bossence is the Vice President of Customer Relations for LeanCor Supply Chain Group.
Founded in 2005, LeanCor is a trusted supply chain partner that delivers operational improvement and measurable financial results. Unlike other third party logistics providers, LeanCor offers a unique combination of third party logistics services, hands-on consulting, and training and education.
Brad has over 14 years of third party logistics experience with a specific focus in Japanese production system environments such as Toyota USA, Toyota Canada, Toyota Europe, Kubota, Yamaha, Suzuki, and Subaru. His previous roles include General Manager of Logistics and Operations at Transfreight as well as various contract and operations management positions across the globe.
As the Vice President of Customer Relations, Brad’s responsibilities have included the vision, leadership and momentum necessary for LeanCor to develop and significantly grow its global customer base. In addition, he has led on a variety of extensive customer projects – most recently with Cummins Inc. in San Luis Potosi, Mexico on a Materials Flow Redesign and Warehouse Relocation. LeanCor is committed to continuous improvement and fully recognizes performance is measured by real results. As an operator and thought leader, LeanCor relentlessly tries to optimize those processes that add value and eliminate those that are waste.
Brad holds a Bachelor of Commerce and an MBA with a focus in International Business and Organizational Behavior from the University of Windsor. He is a certified Professional in Human Resources (PHR), and holds various lean and six sigma accreditations.
Brad resides in Newnan, Georgia with his wife Aubre and their son Townes.
]]>This course will demonstrate how warehouse operations is a key enabler to a successful supply chain implementation and in many cases, the starting point for a transformation. It is critical to manage safety, quality, efficiency and leverage the lean supply chain modifications to improve customer responsiveness and reduce operating costs and in doing so contributing to a supply chain that creates a competitive advantage for a company. To accomplish this goal, we must bring lean principles into the warehouse and distribution center.
Participants receive a course notebook.
None.
Brad Bossence is the Vice President of Customer Relations for LeanCor Supply Chain Group.
Founded in 2005, LeanCor is a trusted supply chain partner that delivers operational improvement and measurable financial results. Unlike other third party logistics providers, LeanCor offers a unique combination of third party logistics services, hands-on consulting, and training and education.
Brad has over 14 years of third party logistics experience with a specific focus in Japanese production system environments such as Toyota USA, Toyota Canada, Toyota Europe, Kubota, Yamaha, Suzuki, and Subaru. His previous roles include General Manager of Logistics and Operations at Transfreight as well as various contract and operations management positions across the globe.
As the Vice President of Customer Relations, Brad’s responsibilities have included the vision, leadership and momentum necessary for LeanCor to develop and significantly grow its global customer base. In addition, he has led on a variety of extensive customer projects – most recently with Cummins Inc. in San Luis Potosi, Mexico on a Materials Flow Redesign and Warehouse Relocation. LeanCor is committed to continuous improvement and fully recognizes performance is measured by real results. As an operator and thought leader, LeanCor relentlessly tries to optimize those processes that add value and eliminate those that are waste.
Brad holds a Bachelor of Commerce and an MBA with a focus in International Business and Organizational Behavior from the University of Windsor. He is a certified Professional in Human Resources (PHR), and holds various lean and six sigma accreditations.
Brad resides in Newnan, Georgia with his wife Aubre and their son Townes.
]]>One of the most misunderstood elements of lean thinking is that lean is primarily about manufacturing. Therefore, we need to be able to answer the question, "How does lean apply to the supply chain?" Connecting lean to supply chain management is the core purpose of this second course in a 3-course series on becoming a Lean Supply Chain professional. Participants will build upon their knowledge from the first course and learn how to apply lean principles and problem solving to supply chain functions.
The overarching theme for the second course is "systems thinking," where we understand how "pull and one piece flow" will lead to reductions to "total cost" of the supply chain. Participants will once again be challenged to question mental models such as economies of scale and replace them with mental models such as economies of time. Having completed the second course, participants will not only be lean problem solvers, they will understand how to connect lean and waste reduction to supply chain functions.
Robert Martichenko is CEO of LeanCor, LLC. He has years of supply chain, logistics and Lean implementation experience. This experience includes multiple Lean Supply Chain implementations supporting successful organizations including Toyota Motor Manufacturing. Robert authored the books "Success in 60 Seconds" and "Everything I know about Lean I Learned in First Grade." He also co-authored the logistics management book "Lean Six Sigma Logistics," published by J. Ross Publishing and co-authored the workbook "Building the Lean Fulfillment Stream," published by the Lean Enterprise Institute. Robert complements his professional experience with a Bachelor Degree in Mathematics from the University of Windsor, an MBA in Finance from Baker College and is a trained Six Sigma Black Belt. He can be reached at RMartichenko@leancor.com.
Brad Bossence is the Vice President of Customer Relations for LeanCor Supply Chain Group.
Founded in 2005, LeanCor is a trusted supply chain partner that delivers operational improvement and measurable financial results. Unlike other third party logistics providers, LeanCor offers a unique combination of third party logistics services, hands-on consulting, and training and education.
Brad has over 14 years of third party logistics experience with a specific focus in Japanese production system environments such as Toyota USA, Toyota Canada, Toyota Europe, Kubota, Yamaha, Suzuki, and Subaru. His previous roles include General Manager of Logistics and Operations at Transfreight as well as various contract and operations management positions across the globe.
As the Vice President of Customer Relations, Brad’s responsibilities have included the vision, leadership and momentum necessary for LeanCor to develop and significantly grow its global customer base. In addition, he has led on a variety of extensive customer projects – most recently with Cummins Inc. in San Luis Potosi, Mexico on a Materials Flow Redesign and Warehouse Relocation. LeanCor is committed to continuous improvement and fully recognizes performance is measured by real results. As an operator and thought leader, LeanCor relentlessly tries to optimize those processes that add value and eliminate those that are waste.
Brad holds a Bachelor of Commerce and an MBA with a focus in International Business and Organizational Behavior from the University of Windsor. He is a certified Professional in Human Resources (PHR), and holds various lean and six sigma accreditations.
Brad resides in Newnan, Georgia with his wife Aubre and their son Townes.
]]>Driven by more frequent and increasingly time definite shipments, global trading partners, complex security and regulatory requirements, volatile fuel costs, new technologies and severe shortages of trained labor in some markets, dealing with the complexities of transportation and distribution planning has become a critical corporate function. This course is focused on understanding capacity development, freight consolidation, network alignment, and synchronization. This course develops the principles, practices, and tools required to address all major issues and tradeoffs in domestic and international transportation including key financial and performance indicators for transportation and design of supply chains to minimize transportation and distribution costs.
Do you work with problems involving the use of material handling equipment in plants, warehouses and other commercial enterprises? All techniques presented are field-proven and derived from successful implementation. Case exercises are adapted from real situations and projects.
Participants receive a course notebook.
H. Lee Hales is President of Richard Muther & Associates. Lee is the author and co-author of several books on industrial planning, including: Systematic Planning of Industrial Facilities (with Richard Muther) and Computer-Aided Facilities Planning.
As a materials and distribution manager, Mr. Hales planned, set up and managed a network of distribution facilities in the oil field equipment industry. In addition to warehousing, he managed purchasing, transportation, and information systems.
As a consultant, Mr. Hales has assisted on a wide range of projects in the US, Asia, Europe, and South America. His clients have included: AGCO, Avon, Caterpillar, Clorox, Motorola, Nokia, General Motors, Ford, Coca-Cola, Fastenal, The Container Store, The Teaching Company, WW Grainger, Delta Air Lines, Glaxo, Philips, Textron, and many others.
Mr. Hales is a Senior Member of the Institute of Industrial Engineers, and past Director of the Facilities Planning & Design Division. Mr. Hales has also served on the College-Industry Council for Material Handling Education, sponsored by the Material Handling Institute. He received B.A. and M.A. degrees from the University of Kansas and holds an M.S. in Management from the Sloan School, Massachusetts Institute of Technology.
]]>Develop effective supply chain performance measurement processes to drive alignment across the corporation. Corporations often struggle with a lack of alignment between financial goals and operational metrics. Additionally, today’s information technology often overwhelms management with data and metrics. In this 3-day course you will learn how to develop metrics that synchronize supply chain and logistics metrics with key company financial metrics and goals. Through coursework and hands-on exercises, students learn to tailor metrics and measurement processes to focus on the most important aspects of the operations and overall corporate goals. As part of the course, performance dashboards from participating student companies and best-in-class organizations will be critiqued. The methods learned in the course are intended to be immediately put to use in the corporate environment.
Participants receive a course notebook.
None.
Maria Rey-Marston successfully combines academic, consulting and applied research activiaties. Her research and consulting focus is on the design and use of performance management systems, both within intra-firm processes and for inter-firm relationships. Her academic and teaching activities are centered on supply chain strategy, outsourcing and inter-firm relationship management, and the strategic connection between supply chain and financial performance.
Since 2012, Maria is Chief Executive Officer of Periphery Labs, a Serenbe GA -based firm that specializes in service innovation and periphery management (networks of external business relationships). She is Senior Advisor with MRM+Partners, leading the Supply Chain Strategy practice of the firm. Her academic and teaching activity is conducted from the Supply Chain & Logistics Institute at Georgia Tech, where she has been affiliated since 1995.
Transforming an organization from traditional thinking to lean thinking requires leadership. This is the third course in a 3-course series on becoming a Lean Supply Chain professional. While the previous courses focus on strategic and tactical implementation of the lean supply chain, this final course "builds" the individual into a lean leader. This transformation is critical to navigate through the waters of change management that is required to successfully execute and sustain the lean supply chain journey.
In the third course participants will complete a deep dive of the concept of House of Lean and explore the main aspects of lean leadership. Among other important topics, participants will learn "go see" management, "A3 thinking" and "leader-as-teacher" concepts.
Robert Martichenko is CEO of LeanCor, LLC. He has years of supply chain, logistics and Lean implementation experience. This experience includes multiple Lean Supply Chain implementations supporting successful organizations including Toyota Motor Manufacturing. Robert authored the books "Success in 60 Seconds" and "Everything I know about Lean I Learned in First Grade." He also co-authored the logistics management book "Lean Six Sigma Logistics," published by J. Ross Publishing and co-authored the workbook "Building the Lean Fulfillment Stream," published by the Lean Enterprise Institute. Robert complements his professional experience with a Bachelor Degree in Mathematics from the University of Windsor, an MBA in Finance from Baker College and is a trained Six Sigma Black Belt. He can be reached at RMartichenko@leancor.com.
Brad Bossence is the Vice President of Customer Relations for LeanCor Supply Chain Group.
Founded in 2005, LeanCor is a trusted supply chain partner that delivers operational improvement and measurable financial results. Unlike other third party logistics providers, LeanCor offers a unique combination of third party logistics services, hands-on consulting, and training and education.
Brad has over 14 years of third party logistics experience with a specific focus in Japanese production system environments such as Toyota USA, Toyota Canada, Toyota Europe, Kubota, Yamaha, Suzuki, and Subaru. His previous roles include General Manager of Logistics and Operations at Transfreight as well as various contract and operations management positions across the globe.
As the Vice President of Customer Relations, Brad’s responsibilities have included the vision, leadership and momentum necessary for LeanCor to develop and significantly grow its global customer base. In addition, he has led on a variety of extensive customer projects – most recently with Cummins Inc. in San Luis Potosi, Mexico on a Materials Flow Redesign and Warehouse Relocation. LeanCor is committed to continuous improvement and fully recognizes performance is measured by real results. As an operator and thought leader, LeanCor relentlessly tries to optimize those processes that add value and eliminate those that are waste.
Brad holds a Bachelor of Commerce and an MBA with a focus in International Business and Organizational Behavior from the University of Windsor. He is a certified Professional in Human Resources (PHR), and holds various lean and six sigma accreditations.
Brad resides in Newnan, Georgia with his wife Aubre and their son Townes.
]]>Presentation Title: A World Class Supply Chain that Delivers Sustainable and Profitable Growth
Abstract:
Unilever's vision is to double the size of the business, whilst reducing its environmental footprint and increasing its positive social impact. The supply chain, through its unique model of leveraging global scale whilst maintaining local agility, through a set of world class capabilities is proving to be a true competitive advantage for the business and recognized externally too. The main focus of the presentation will be how the supply chain is at the heart of Unilever's world renowned sustainability program and how it is driving the frontiers of sustainability and positive social impact to make the world a better place.
Bio:
Pier Luigi Sigismondi joined Unilever and its Executive Board (UEx) in September 2009. As Chief Supply Chain Officer he heads a global operation consisting of 270 factories delivering €23bn of cost of goods sold. He is accountable for Unilever's end to end value chain and tasked with creating the best Supply Chain in the FMCG industry. Pier Luigi Sigismondi was appointed as a Non-Executive Member of the Supervisory Board of Rexel in May 2013.
Pier Luigi is a Computer & Engineering scientist and holds a Masters of Science in Industrial Engineering from the Georgia Institute of Technology in Atlanta, Georgia. Pier Luigi started his career with Booz Allen & Hamilton as an industrial engineer and worked in several industries (aerospace, automotive and appliances among others), heading several multi-national assignments in the US and Europe.
He joined global management consultancy A T Kearney in 1997 and became Vice President of operations in Italy. Focusing on strategic procurement, manufacturing and logistics across industries, including fast-moving consumer goods, appliances and retail, he led numerous assignments in South East Asia, Europe and the Americas. In 2002, Pier Luigi joined Nestlé SA as Vice President of Corporate Operations Strategies, based in Switzerland. He was responsible for industrial strategies and the restructuring of the group worldwide, as well as for management of global cost improvement programmes. Pier Luigi led the Innovation Acceleration initiatives for Nestlé across all the business categories. He moved to Nestlé Mexico in 2005 as Vice President of Supply Chain and R&D.
Pier Luigi has attended the Management Development Programme at S. Gallen University and the Senior Programme for Leadership Development at London Business School, as well as IMD.
Married with three daughters, Pier Luigi's main interests are flying planes, sports, and reading.
]]> Mon., March 31
• Payments can be made via journal entry. Otherwise, make checks payable to
“Faculty & Staff Honors Luncheon.”
• Reservation and payment instructions are also posted online at
www.specialevents.gatech.edu/honorsluncheon.
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404-894-7613
]]>SPEAKER: Salal Humair
ABSTRACT:
The fight against HIV has been a hallmark of global health efforts in the last decade. This fight takes place in an environment where evidence, advocacy and policy continually push and pull each other—new evidence about the efficacy of HIV interventions emerges at a rapid pace; pressure for revising policies grows quickly from advocacy groups; and policy makers struggle to manage aspirations within available resources. In this environment, models can help illuminate debates about better use of resources when considering new policies.
For instance, widely-celebrated evidence emerged in 2011 from a randomized controlled trial showing that antiretroviral treatment (ART), used for reducing mortality and morbidity in patients at a relatively advanced stage of HIV, can reduce HIV transmission by as much as 96% if given to patients at a less advanced stage. This was quickly hailed as a game-changer in the fight against HIV, resulting in significant pressure for using ART for prevention (coined treatment-as-prevention or TasP). Policy makers worried about the additional resources that would be needed, but modeling studies argued that TasP is worthwhile, as it will be cost-effective compared to an absolute benchmark of an intervention’s cost-effectiveness (e.g. three times the GDP per capita). I will present a model that allowed us to assess the cost-effectiveness of TasP not against an absolute benchmark but against combinations of other existing HIV interventions, such as ART and medical male circumcision. This model offered a valuable counter-argument to the prevailing narrative and found traction with policy makers.
A broader, and continuing, debate among HIV policy makers concerns allocative efficiency – how to optimally allocate resources among different HIV prevention and treatment interventions over time. While models have addressed optimal allocation of resources between different HIV treatment interventions, or between different HIV prevention interventions, consideration of treatment and prevention together is rare. This is partly because treatment and prevention are viewed as having different objectives—reducing mortality and morbidity vs. averting new infections—so it is not clear how to combine both. Studies based on cost-effectiveness typically suggest putting all resources into prevention, a result difficult to justify in practice. I will present a model in which we formulated the optimal allocation problem in a manner which reveals intuitively and practically appealing results. I will present insights from analysis of simple versions of the model, as well as the results of a computational model built from insights obtained from simpler cases.
I will end the talk by mentioning the breadth of opportunities that exist for modeling in the area of HIV as well as global health in general.
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SPEAKER: Arman Sabbaghi
ABSTRACT:
Potential outcomes provide a powerful framework for addressing problems in causal inference. Although used extensively in observational studies, their power has not been fully appreciated in experimental design since the time of Neyman and Kempthorne. The key aspect of my research is the application of potential outcomes for a wide range of theoretical and applied problems in experimental design and statistics. This is illustrated by means of two problems, one classical and the other involving a cutting-edge application in engineering.
The first part of this talk will address the Neyman-Fisher controversy, which originated with the 1935 presentation of Jerzy Neyman's Statistical Problems in Agricultural Experimentation to the Royal Statistical Society. Neyman asserted that the standard ANOVA F-test for randomized complete block designs is valid, whereas the analogous test for Latin squares is invalid in the sense of detecting differentiation among the treatments, when none existed on average, more often than desired (i.e., having a higher Type I error than advertised). However, Neyman's expressions for the expected mean residual sum of squares, for both designs, are generally incorrect. Furthermore, Neyman's belief that the Type I error (when testing the null hypothesis of zero average treatment effects) is higher than desired whenever the expected mean treatment sum of squares is greater than the expected mean residual sum of squares, is generally incorrect. It is shown that without further assumptions on the potential outcomes, one cannot determine the Type I error of the F-test from expected sums of squares.
The second part will present a novel application of potential outcomes for quality control in 3D printing, a promising manufacturing technique marred by product deformation due to material solidification in the printing process. Control of printed product deformation can be achieved by a compensation plan. However, little attention has been paid to interference in compensation, which is thought to result from the inevitable discretization of a compensation plan. We investigate interference with an experiment involving the application of discretized compensation plans to cylinders. Our treatment illustrates how the potential outcomes framework improves our ability to understand and model interference by means of graphical posterior predictive checks, which in turn facilitates the study of printed product deformation under discretized compensation plans. Properly defining experimental units and understanding interference are critical for quality control in complex manufacturing processes. The potential outcomes framework ultimately provides a step in that direction for 3D printing.
SPEAKER: Natashia Boland
ABSTRACT:
Mining and water are two areas of national importance to Australia, the former for its economic importance and the latter for its growing scarcity. An optimization problem arising in each of these settings will be considered. In mining, the problem concerns scheduling maintenance on transport and logistics equipment in a coal export supply chain so as to minimize the impact of maintenance activities on the throughput of the system. In water, the problem is how best to manage water allocated to the environment under Australia's regulatory framework. These applications highlight the need to solve integer programs with multiple objectives. We will present new methods for biobjective integer programming that exploit the power of modern MIP solvers. The resulting methods deduce the efficient frontier in a computationally effective way. One of the features exploited in these methods is the ability of solvers to make use of high quality feasible solutions. Alternating projection algorithms have been of increasing interest as heuristics for MIPs, and more broadly for discrete optimization problems. However, little is known about the theoretical properties of such algorithms in these settings. We mention some recent advances in this direction, and demonstrate algorithmic improvements.
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