报告题目: Augmenting Simulation Metamodels with Direct Gradient Estimators

报告人: Prof. Michael Fu
Decision and Information Technologies Department, Robert H. Smith School of Business,
Institute for Systems Research, Department of Electrical and Computer Engineering,
University of Maryland (College Park).

报告时间：6月7日 星期五 下午2:00
报告地点：浙江大学 工控所 老楼 414会议室
主持人: 宋春跃

报告摘要:
Traditional metamodel-based optimization methods assume experiment data collected consist of performance measurements only, reflecting the roots of actual physical experimentation. However, in many settings involving stochastic simulation experiments, direct gradient estimates are available. We investigate techniques that augment existing regression and stochastic kriging models to incorporate additional gradient information. The augmented models are shown to be compelling compared to existing models, in the sense of improved accuracy or reducing simulation cost. Numerical results also indicate that the augmented models can capture trends that standard models miss.

报告人简介:
Dr. Fu is Tyser Professor of Management Science, Decision and Information Technologies Department, Robert H. Smith School of Business, joint appointment with the Institute for Systems Research, affiliate appointment with the Department of Electrical and Computer Engineering, University of Maryland (College Park).

Dr. Fu received his M.S. and PhD. degrees in applied mathematics from Harvard University in 1986 and 1989, respectively. He received S.B. and S.M. degrees in electrical engineering and a S.B. degree in mathematics from the Massachusetts Institute of Technology in 1985. Dr. Fu is a fellow of IEEE and INFORMS. He served as a Program Director for Operations Research in the National Science Foundation’s Division of Civil, Mechanical and Manufacturing Innovation for 2010�C2012. More details can be found at http://www.rhsmith.umd.edu/faculty/mfu/fu.htm