| Chun-Hung Chen
乔治梅森大学 & 国立台湾大学教授
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【主讲】Chun-Hung Chen 乔治梅森大学 & 国立台湾大学教授
【时间】2013-10-30（周三）15:00-16:30
【摘要】Simulation and optimization are two arguably most used operations research tools. Stochastic simulation is a powerful tool for analyzing modern complex systems. Detailed dynamics of complex, stochastic systems can be modeled in simulation. This capability complements the inherent limitation of traditional optimization, so the combining use of simulation and optimization is growing in popularity. This seminar discusses what computational issues we have to face such a combination, and presents our new development to address these issues. A key component of our methodologies is a new technique called Optimal Computing Budget Allocation (OCBA) initially developed by the speaker, which intends to maximize the overall simulation or sampling efficiency for finding an optimal decision. OCBA also provides a good solution to the well-known exploration (search) vs. exploitation (estimation) tradeoff. Further, OCBA can optimally determine the allocation of samples for partition-based random search algorithms.
【演讲人简历】Chun-Hung Chen received his Ph.D. degree in Engineering Sciences from Harvard University in 1994. He is currently a Professor at George Mason University and National Taiwan University. Dr. Chen was an Assistant Professor of Systems Engineering at the University of Pennsylvania before joining GMU. Sponsored by NSF, NIH, DOE, NASA, MDA, Air Force, and FAA, he has worked on the development of very efficient methodology for stochastic simulation optimization and its applications. Dr. Chen received a “National Thousand Talents Award” (“千人计划” 国家特聘专家) in 2011, the Best Automation Paper Award from the 2003 IEEE International Conference on Robotics and Automation, 1994 Eliahu I. Jury Award from Harvard University, and the 1992 MasPar Parallel Computer Challenge Award. He has served as a department editor for IIE Transactions, associate editor of IEEE Transactions on Automatic Control, associate editor of IEEE Transactions on Automation Science and Engineering, area editor of Journal of Simulation Modeling Practice and Theory, and associate editor of International Journal of Simulation and Process Modeling.
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