【学术讲座】黄文杰:Preference Robust Optimization: Characterization and Numerical (5月19日)

  • 日期:2021-05-08

 

讲座题目:Preference Robust Optimization: Characterization and Numerical Methods

 

主讲嘉宾:黄文杰博士  香港中文大学(深圳)数据科学学院、蒙特利尔高等商学院决策分析研究中心

 

讲座时间:2021年5月19日10:00-12:00

 

讲座地点:中国科学院大学关村教学楼N406

 

Abstract:

In behavior economics, a decision maker’s (DM) preference over prospects can be expressed by choice functions (e.g., utility function and risk measure). In this work, we study preference robust optimization (PRO) problems where robust optimal decision should be made with ambiguous choice function of DM and its partial information can be elicited. We show novel ways of defining and formulating multi-attribute quasi-concave choice functions. Mathematical tractability schemes and new decision analysis foundations. are illustrated. Efficient numerical methods are developed where the robust choice function and the PRO problem can be constructed and solved by a sequence of linear programs/convex optimization problems. Finally, we test the behavior and scalability of our method numerically on a homeland security budget allocation problem and a portfolio optimization problem.

 

Bio:

黄文杰,博士,香港中文大学(深圳)数据科学学院和加拿大蒙特利尔高等商学院决策分析研究中心的国际博士后(导师:王子卓,Erick Delage),分别于上海交通大学工业工程系和新加坡国立大学工业系统工程与管理系获得学士学位(2014年)和博士学位(2019年)。2018-2019年曾兼任新加坡国立大学工业系统工程与管理系的研究工程师。研究方向专注于:随机/鲁棒优化、强化学习、数据驱动决策的基础理论,并在风险管理、运营管理及城市可持续发展等领域有应用。在IEEE Transactions on Automatic Control, IEEE Transactions on Engineering Management, AAAI Conference on Artificial Intelligence,IEEE Conference on Decision and Control等国际顶级期刊和会议上发表多篇论文。担任Production and Operations Management等国际顶级期刊和会议的审稿人。