Retrospective Optimization for Stochastic Systems

报告题目：Retrospective Optimization for Stochastic Systems

报 告 人：王洪刚 助理教授（Rutgers University）

报告时间：2017年7月7日10：00

报告地点：南一楼中311室

摘要：In this talk, I will share my research work including methodology and application in simulation based optimization. I will first present R-SPLINE (Retrospective Optimization using Simplex Linear Interpolation and Neighborhood Evaluation) for integer simulation optimization problems. R-SPLINE is a stochastic optimization framework with sequential data-driven approximations and guarantees almost-sure convergence under certain conditions. I will also talk about new multi-objective optimization ideas using zigzag search for multi-criteria decision making under systems uncertainty. Numerical results based on a number of energy production and micro-grid power cases are shown to demonstrate the efficiency of the discussed algorithms.

个人简介: Honggang Wang is assistant professor in Industrial and Systems Engineering at Rutgers University. He received his Bachelor of Science degree in Power Engineering from Shanghai Jiao Tong University, Shanghai, China, in 1996, Master of Science in Manufacturing Engineering from University of Missouri-Rolla, in 2004, and Ph.D. in Operations Research from Purdue University, West Lafayette IN, in 2009. He had worked as a Postdoctoral Scholar in Energy Resources Engineering at Stanford University for two years before he joined Rutgers, NJ in 2011. Dr. Wang has won IBM faculty award 2012 and faculty award from Tracy Energy LLC for his work in petroleum and energy projects. He has won 2016 best paper award at Geothermal Research Council annual meeting, Sacramento CA, USA.