报告题目：Data-Driven Markov Decision Processes with Parameter Uncertainty: Application to Remanufacturing Planning

报告所属学科：管理科学与工程

报告人：向一莎（美国休斯敦大学（University of Houston））

报告时间：2022年12月21日 10:00-11:30

报告地点：腾讯会议: 283-848-502

报告摘要：

We consider the problem of remanufacturing planning with the objective of minimizing the negative environmental impacts while sustaining profitable growth. Determining the optimal remanufacturing timing, first and foremost, requires modeling of the state transitions of a system. The estimation of these probabilities, however, often suffers from data inadequacy and is far from accurate, resulting in serious degradation in performance. To mitigate the impacts of the uncertainty in transition probabilities, we develop a novel data-driven modeling framework for remanufacturing planning in which decision makers can remain robust with respect to statistical estimation errors. We model the remanufacturing planning problem as a robust Markov decision process, and construct ambiguity sets that contain the true transition probability distributions with certainty using historical data. We further establish structural properties of optimal robust policies and insights for remanufacturing planning. A computational study on the NASA turbofan engine shows that our data-driven decision framework consistently yields better worst-case performances and higher reliability of the performance guarantee.

报告人简介：

Dr. Yisha Xiang is the associate professor of Industrial Engineering at the University of Houston. Her current research and teaching interests involves data-driven decision-making under uncertainty and statistical machine learning. Her research has been funded by National Science Foundation, including a CAREER grant, and industry. She has published articles in refereed journals, such as INFORMS journal on computing, IISE Transactions, European Journal of Operational Research, and Naval Research Logistics. She was the recipient of the P.K. McElroy award, Stan Oftshun award, and Doug Ogden award for best papers at the Reliability and Maintainability Symposium. Dr. Xiang received her B.S. in Industrial Engineering from Nanjing University of Aero. & Astro., China, and M.S and Ph.D. in Industrial Engineering from University of Arkansas. She serves as an Associate Editor for IISE Transactions and IEEE Transactions Automation Science and Engineering. She also currently serves as the Chair-elect of the INFORMS Quality, Statistics, and Reliability Sector, and President-elect of the IISE Quality Control and Reliability Engineering Division. She is a member of IISE and INFORMS.