一、主题：Multi-component Maintenance Optimization: A Stochastic Programming Approach
二、主讲人：美国德州理工大学Yisha Xiang 助理教授
Maintenance optimization has been extensively studied in the past decades. However, most of the existing maintenance models focus on single-component systems and are not applicable for complex systems consisting of multiple components, due to various interactions between the components. Multi-component maintenance optimization problem, which joins the stochastic processes regarding the failures of the components with the combinatorial problems regarding the grouping of maintenance activities, is challenging in both modeling and solution techniques, and has remained as an open issue in the literature. In this paper, we study the multi-component maintenance problem over a finite planning horizon and formulate the problem as a multi-stage stochastic integer program with decision-dependent uncertainty. Structural properties of the two-stage problem are investigated, and a progressive-hedging-based heuristic is developed based on the structural properties. Our heuristic algorithm demonstrates a significantly improved capacity in handling practically large-size two-stage problems comparing to three conventional methods for stochastic integer programming, and solving the two-stage model by our heuristic in a rolling horizon provides a good approximation of the multi-stage problem. The heuristic is further benchmarked with a dynamic programming approach commonly adopted in the literature. Numerical results show that our heuristic can lead to significant cost savings compared with the benchmark approach.
Dr. Yisha Xiang is an Assistant Professor in the Department of Industrial, Manufacturing & Systems Engineering at Texas Tech University. She 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. Dr.Xiang’s current research and teaching interests involves reliability modeling and optimization, maintenance optimization, and risk analysis. She has published articles in refereed journals, such as IIE Transactions, European Journal of Operational Research, and Computers and Industrial Engineering. She received the prestigious Ralph A. Evans/P.K. McElroyy Award for the best paper at the 2013 Reliability and Maintainability Symposium, and Stan Oftshun Best Paper Award from Society of Reliability Engineers in 2013 and 2017. She is a member of SRE, IIE and INFORMS.