{"60532":{"#nid":"60532","#data":{"type":"event","title":"Advances in multistage optimization","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETITLE:\u003C\/strong\u003E\u0026nbsp; Advances in multistage optimization\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ESPEAKER:\u003C\/strong\u003E\u0026nbsp; Dimitris Bertsimas (Boeing Prof. of OR)\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EABSTRACT:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EIn this presentation, we show a significant role that symmetry, a\nfundamental\nconcept in convex geometry, plays in determining the power of robust\nand\nfinitely adaptable solutions in multi-stage stochastic and adaptive\noptimization problems. We consider a fairly general class of\nmulti-stage mixed\ninteger stochastic and adaptive optimization problems and propose a\ngood\napproximate solution policy with performance guarantees that depend on\nthe\n\u003Cbr \/\u003E\ngeometric properties such as symmetry of the uncertainty sets. In\nparticular,\nwe show that a class of finitely adaptable solutions is a good\napproximation\nfor both the multi-stage stochastic as well as the adaptive\noptimization\nproblem. A finitely adaptable solution specifies a small set of\nsolutions for\neach stage and the solution policy implements the best solution from\nthe given\n\u003Cbr \/\u003E\nset depending on the realization of the uncertain parameters in the\npast\nstages. To the best of our knowledge, these are the first approximation\nresults\nfor the multi-stage problem in such generality.\u0026nbsp;\u0026nbsp;\u0026nbsp;\n(joint work with Vineet Goyal, Columbia University and Andy Sun, MIT)\u003Cbr \/\u003E\n\u003Cbr \/\u003E\nBio:\u003Cbr \/\u003E\n\u003Cbr \/\u003E\nDimitris Bertsimas is currently the Boeing Professor of Operations\nResearch\u0026nbsp;\nand the\u003Cbr \/\u003E\ncodirector of the Operations Research Center\u0026nbsp;\nat the Massachusetts Institute\u0026nbsp;\nof Technology.\u003Cbr \/\u003E\nHe has\u0026nbsp; received a BS\u0026nbsp;\u0026nbsp; in\u0026nbsp;\nElectrical Engineering and Computer Science at the National\u003Cbr \/\u003E\nTechnical\u0026nbsp;\nUniversity of Athens, Greece in 1985, a MS\u0026nbsp; in Operations Research\u0026nbsp;\nat MIT\u0026nbsp; in\u003Cbr \/\u003E\n1987, and a Ph.D in Applied\u0026nbsp;\nMathematics and Operations Research at MIT in 1988.\n\u003Cbr \/\u003E\nSince 1988, he has been in the MIT faculty.\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Advances in multistage optimization"}],"uid":"27187","created_gmt":"2010-08-23 11:00:27","changed_gmt":"2016-10-08 01:52:11","author":"Anita Race","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2010-09-14T12:00:00-04:00","event_time_end":"2010-09-14T13:00:00-04:00","event_time_end_last":"2010-09-14T13:00:00-04:00","gmt_time_start":"2010-09-14 16:00:00","gmt_time_end":"2010-09-14 17:00:00","gmt_time_end_last":"2010-09-14 17:00:00","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":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}