Designing and operation of complex large-scale systems such as transportation systems, manufacturing systems, supply chain networks, and health care systems are very difficult tasks. Many contributing factors exist; chief among them is the exponential explosion of alternatives normally leading to NP-hard optimization problems. In the case of stochastic optimization, the situation is further complicated by randomness. We have recently developed a new framework called Nested Partitions (NP) for global optimization. NP uses partitioning, random sampling, selection of a promising index, and backtracking techniques to create a Markov chain, which has been proven with probability one to converge to a global optimum. One important feature of the NP method is that it can combine global search and local search (domain knowledge or heuristic) procedures in a natural way. The NP method is also highly matched to massively parallel processing capabilities. The global and parallelism nature of the optimization framework provides an efficient and effective platform for information sharing and exchange during search procedure. In this talk, we will introduce the NP framework, discuss related theoretical issues, and demonstrate its effectiveness through a few application examples.

LEYUAN SHI is a Professor in the Department of Industrial and Systems Engineering at University of Wisconsin-Madison. She received her Ph.D. in Applied Mathematics from Harvard University in 1992. Her research interests include simulation modeling and large-scale optimization with applications to operation planning and scheduling, supply chain management, transportation, and health care systems. She has developed a novel optimization framework, the Nested Partitions Method that has been applied to many large-scale and complex systems optimization problems. This research work has been funded by NSF, AFSOR, ONR, State of Wisconsin, and many private industrial companies with a total funding in excess of 6 millions. Her research work has been published on journals such as Operations Research, Management Science, JDEDS, IIE Trans. and IEEE Trans. She is currently serving on editorial board for IEEE Trans on Automation Science and Engineering, Journal of Discrete Event Dynamic Systems, INFORMS Journal on Computing, and Journal of Methodology, and Computing in Applied Probability. She served on editorial board for Manufacturing & Service Operations Management. She also served as General Chair, co-Chair, and program committee for many national and international conferences. She chairs the Outstanding Publication Award Committee for the INFORM College on Simulation. She is the recipient of the Vilas Associate Award in 2006.