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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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Complex systems consisting of a large number of interacting components are in practice increasingly modeled through computer simulations rather than via traditional equation based approaches. The resulting model typically allows for little or no structural assumptions on the form of the objective function or constraints, thus posing a challenging optimization problem. We explore in this talk a novel optimization paradigm inherited from game theory that animates the components of the system within a non-cooperative game of identical interest. The optimizations take place though individual best replies of the players, thus vastly reducing the dimensionality of the optimization problems solved (the components' joint interactions are reflected indirectly through their shared objective function). We will illustrate the approach by discussing an application to a joint production systems optimization project within the GM Collaborative Research Laboratory at the University of Michigan.
Dr. Smith received his Ph.D. in Engineering Science from the University of California at Berkeley where he held an NSF Fellowship. He holds a bachelors degree in Physics from Harvey Mudd College and an MBA from Berkeley. He is currently the Altarum/ERIM Russell D. O'Neal Professor of Engineering at the University of Michigan, Ann Arbor. He has been a visiting professor at the Statistical Laboratory, University of Cambridge; the Faculty of Systems Theory and Operations Research, Delft University of Technology, The Netherlands; the Department of Industrial Engineering and Operations Research, Columbia University; the Econometric Institute, Erasmus University, Rotterdam, The Netherlands; Laboratoire d'Automatique et d'Analyse du Systems du CNRS, Toulouse, France; the Faculty of Industrial Engineering and Management, Technion, Haifa, Israel; the Mathematical Sciences Research Institute, Berkeley, California; the Operations Research Group, Institute of Pure and Applied Mathematics, Rio de Janeiro, Brazil; the Department of Industrial Engineering and Operations Research, University of California, Berkeley. He is the receipient of the first Altarum/ERIM Russell D. O'Neal Professorship of Engineering at the University of Michigan. He has also been honored with the Distinguished Faculty Achievement Award from the University of Michigan, the College of Engineering Research Excellence Award, an Outstanding Teacher Award from the Michigan Student Assembly, and a National Science Foundation Fellowship. He is a Fellow of the Institute for Operations Research and the Management Sciences. Dr. Smith teaches courses in dynamic programming and stochastic processes. He has supervised the doctoral research of over twenty-one students since 1984. Dr. Smith is Director of the Dynamic Systems Optimization Laboratory at the University of Michigan. The Laboratory research is directed toward the modeling and analysis of dynamical systems over time. He is also the UM Thrust Leader for Manufacturing Systems for the General Motors Collaborative Research Laboratory in Advanced Vehicle Manufacturing at the University of Michigan. Dr. Smith worked earlier at Bell Laboratories in the Network Planning Department where he developed models and algorithms for optimal routing of communications traffic. He is currently project director on three NSF Grants in global and infinite horizon optimization within the Operations Research and Manufacturing Enterprise Systems Programs of the National Science Foundation. Dr. Smith is a Past Associate Editor of Management Science, Chairman of the 2003 Dantzig Dissertation Prize Committee, and is the author of over eighty peer reviewed publications.
