Dimitris Bertsimas, MIT

Event Details
  • Date/Time:
    • Tuesday September 14, 2010
      11:00 am - 12:00 pm
  • Location: Executive classroom
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    N/A
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Contact

Renato Monteiro, ISyE
Contact Renato Monteiro
404-894-2300

Summaries

Summary Sentence: Advances in multistage optimization (Joint OR/ACO Colloqium)

Full Summary: In this presentation, we show a significant role that symmetry, a fundamental concept in convex geometry, plays in determining the power of robust and finitely adaptable solutions in multi-stage stochastic and adaptive optimization problems. We consider a fairly general class of multi-stage mixed integer stochastic and adaptive optimization problems and propose a good approximate solution policy with performance guarantees that depend on the geometric properties such as symmetry of the uncertainty sets. In particular, we show that a class of finitely adaptable solutions is a good approximation for both the multi-stage stochastic as well as the adaptive optimization problem. A finitely adaptable solution specifies a small set of solutions for each stage and the solution policy implements the best solution from the given set depending on the realization of the uncertain parameters in the past stages. To the best of our knowledge, these are the first approximation results for the multi-stage problem in such generality.

Speaker

Boeing Leaders for Global Operations Professor
Operations Research/Statistics
Sloan School of Management

Abstract

In this presentation, we show a significant role that symmetry, a fundamental concept in convex geometry, plays in determining the power of robust and finitely adaptable solutions in multi-stage stochastic and adaptive optimization problems. We consider a fairly general class of multi-stage mixed integer stochastic and adaptive optimization problems and propose a good approximate solution policy with performance guarantees that depend on the geometric properties such as symmetry of the uncertainty sets. In particular, we show that a class of finitely adaptable solutions is a good approximation for both the multi-stage stochastic as well as the adaptive optimization problem. A finitely adaptable solution specifies a small set of solutions for each stage and the solution policy implements the best solution from the given set depending on the realization of the uncertain parameters in the past stages. To the best of our knowledge, these are the first approximation results for the multi-stage problem in such generality.

(joint work with Vineet Goyal, Columbia University and Andy Sun, MIT)

Bio

Dimitris Bertsimas is currently the Boeing Professor of Operations Research and the codirector of the Operations Research Center at the Massachusetts Institute of Technology. He has received a BS in Electrical Engineering and Computer Science at the National Technical University of Athens, Greece in 1985, a MS in Operations Research at MIT in 1987, and a Ph.D in Applied Mathematics and Operations research at MIT in 1988. Since 1988, he has been in the MIT faculty.

His research interests include optimization, stochastic systems, data mining, and their application. He has co-authored more than 120 scientific papers and he has co-authored the following books: ``Introduction to Linear Optimization'' (with J. Tsitsiklis, Athena Scientific and Dynamic Ideas, 2008), ``Data, models and decisions'' (with R. Freund, Dynamic Ideas, 2004) and ``Optimization over Integers'' (with R. Weismantel, Dynamic Ideas, 2005). He is currently department editor in Optimization for Management Science and former area editor in Operations Research in Financial Engineering. He has supervised 42 doctoral students and he is currently supervising 10 others.

He is a member of the National Academy of Engineering, and he has received several research awards including: the Farkas prize (2008), the Erlang prize (1996), the SIAM prize in optimization (1996), the Bodossaki prize (1998) and the Presidential Young Investigator award (1991-1996).

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H. Milton Stewart School of Industrial and Systems Engineering (ISYE)

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Status
  • Created By: Mike Alberghini
  • Workflow Status: Published
  • Created On: Dec 20, 2012 - 10:40am
  • Last Updated: Oct 7, 2016 - 10:01pm