{"661777":{"#nid":"661777","#data":{"type":"event","title":"ISyE Seminar -  Prof. J. Cole Smith","body":[{"value":"\u003Ch3\u003ETitle:\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EAsymmetric Stochastic Shortest-Path Interdiction Favoring the Evader\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u0026nbsp;\u003Cbr \/\u003E\r\nAbstract:\u0026nbsp;\u003C\/h3\u003E\r\n\r\n\u003Ch3\u003EThis work was completed with Dr. Di Nguyen, a professor at University College Dublin. We discuss a two-stage shortest-path interdiction problem between an interdictor and\u0026nbsp;an evader, in which the cost for an evader to use each arc is given by the arc\u0026rsquo;s\u0026nbsp;base\u0026nbsp;cost plus an additional cost if the arc is attacked by the interdictor. The interdictor\u0026nbsp;acts first to attack a subset of arcs, and\u0026nbsp;then the evader traverses the network using a\u0026nbsp;shortest path. In the problem we study, the interdictor does not know the exact\u0026nbsp;value of\u0026nbsp;each base cost, but instead only knows the (nonnegative uniform) distributions of each\u0026nbsp;arc\u0026rsquo;s base cost. The evader\u0026nbsp;observes both the subset of arcs attacked by the interdictor\u0026nbsp;and the true base cost values before traversing the network, and is\u0026nbsp;thus at an advantage. The interdictor seeks to\u0026nbsp;maximize evader\u0026rsquo;s shortest-path costs, but the choice of objective is a key\u0026nbsp;consideration. We examine ideas underscoring how the interdictor could maximize the expected objective that an evader will incur,\u0026nbsp;and then more generally explore the maximization of the evader\u0026rsquo;s conditional value-at-risk, given some specified risk parameter.\u0026nbsp;\u003Cbr \/\u003E\r\n\u0026nbsp;\u003Cbr \/\u003E\r\nBio sketch:\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;Dr. J. Cole Smith is\u0026nbsp;Dean\u0026nbsp;of the College of Engineering and Computer Science at Syracuse University. Prior to that role,\u0026nbsp;he served as an Associate Provost for Academic Initiatives and as Department Chair of Industrial Engineering at Clemson University.\u0026nbsp;His research regards mathematical optimization models and algorithms, especially those arising in combinatorial optimization. Dr.\u0026nbsp;Smith\u0026rsquo;s awards include the Young Investigator Award from the ONR, the Hamid K. Elden Outstanding Young Industrial Engineer in\u0026nbsp;Education award, the Operations Research Division Teaching Award, the 2014 Glover-Klingman prize for best paper in Networks,\u0026nbsp;and the best paper award from IIE Transactions in 2007. He became a Fellow of IISE in 2018, and serves as the INFORMS Vice\u0026nbsp;President of Publications.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Ch3\u003E\u003Cstrong\u003EAbstract:\u0026nbsp;\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThis work was completed with Dr. Di Nguyen, a professor at University College Dublin. We discuss a two-stage shortest-path interdiction problem between an interdictor and\u0026nbsp;an evader, in which the cost for an evader to use each arc is given by the arc\u0026rsquo;s\u0026nbsp;base\u0026nbsp;cost plus an additional cost if the arc is attacked by the interdictor. The interdictor\u0026nbsp;acts first to attack a subset of arcs, and\u0026nbsp;then the evader traverses the network using a\u0026nbsp;shortest path. In the problem we study, the interdictor does not know the exact\u0026nbsp;value of\u0026nbsp;each base cost, but instead only knows the (nonnegative uniform) distributions of each\u0026nbsp;arc\u0026rsquo;s base cost. The evader\u0026nbsp;observes both the subset of arcs attacked by the interdictor\u0026nbsp;and the true base cost values before traversing the network, and is\u0026nbsp;thus at an advantage. The interdictor seeks to\u0026nbsp;maximize evader\u0026rsquo;s shortest-path costs, but the choice of objective is a key\u0026nbsp;consideration. We examine ideas underscoring how the interdictor could maximize the expected objective that an evader will incur,\u0026nbsp;and then more generally explore the maximization of the evader\u0026rsquo;s conditional value-at-risk, given some specified risk parameter.\u0026nbsp;\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\n\u0026nbsp;\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Asymmetric Stochastic Shortest-Path Interdiction Favoring the Evader"}],"uid":"36374","created_gmt":"2022-10-03 14:25:30","changed_gmt":"2022-10-06 14:46:21","author":"mwelch39","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-10-07T12:30:00-04:00","event_time_end":"2022-10-07T13:30:00-04:00","event_time_end_last":"2022-10-07T13:30:00-04:00","gmt_time_start":"2022-10-07 16:30:00","gmt_time_end":"2022-10-07 17:30:00","gmt_time_end_last":"2022-10-07 17:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}