題目：隨機系統的回顧性優化

報告人：王洪剛

時間：2017.7.3下午3：30-4：30

地點：經管學院435

Talk: Retrospective Optimization for Stochastic SystemsIn 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.

講座摘要：隨機系統的回顧性優化在這次演講中，我將分享我的研究工作，包括基于模擬優化的方法和應用。 我將首先提出R-SPLINE（使用線性插值和鄰域評估的回顧性優化），用于整數模擬優化問題。 R-SPLINE是一種隨機優化框架，具有依序數據驅動的近似，并保證在某些條件下幾乎肯定的收斂。 我還將介紹一種新的多目標優化想法：使用之字形優化在系統不確定性下的多標準決策。我們會討論一些能源開發，微電網管理控制的實例。通過這些例子，我們展示了所開發的隨機模型和優化方法的高效性。

Bio: 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.

簡歷：王洪剛是羅格斯大學工業與系統工程系助理教授。 他于1996年獲得上海交通大學機械動力工程學士學位，2004年獲密蘇里大學羅拉大學制造工程科學碩士學位，2009年獲普渡大學工業工程博士學位。他在斯坦福大學能源資源工程博士后工作兩年，之后于2011年加入羅格斯新澤西州立大學。王博士榮獲2012年IBM教授獎。 他在美國地熱研究委員會2016年度會議獲得最佳論文技術獎。