讲座时间：8月14日10:00-12:30

讲座地点：管楼506会议室

讲座主题：Mitigating Supply Disruption with Flexible and Adaptive Operations

讲座嘉宾简介

Dr. Sun Qinghe is an Assistant Professor in the Department of Logistics and Maritime Studies at The Hong Kong Polytechnic University, Faculty of Business. Prior to this, she earned her Ph.D. in Operations Research and Analytics from the National University of Singapore and BSc in Maritime Studies (1st Class Hons) from Nanyang Technological University. Her research focuses on analytics and optimization under uncertainty, data-driven decision-making, and their applications in transportation, maritime logistics and supply chain systems. Her work has been published in leading journals, such as Transportation Research Part B, Operations Research, and Production and Operations Management, among others.

讲座摘要

This talk presents two studies on mitigating supply disruptions through flexibility and adaptive decision-making in manufacturing systems and emergency logistics.

The first study examines process flexibility, a well-established strategy for managing demand uncertainty, as a tool for mitigating supply disruptions in long chain systems. We derive a closed-form, tight bound on the expected sales ratio of a long chain relative to full flexibility under random disruptions, offering a service level guarantee. The results show that long chains achieve notable resilience by leveraging their sparsity to absorb unexpected disruptions. To generalize these findings, we introduce a moment decomposition approach that extends to general piecewise polynomial performance metrics while remaining tractable via a semidefinite program (SDP).

The second study examines emergency operations, where disruptions such as facility closures occur before demand fluctuations materialize, requiring adaptive decisions under partial information. We propose a three-stage robust optimization model with a binary uncertainty set for disruptions and a mean–covariance ambiguity set for demand uncertainty. To overcome the computational complexity of the resulting min–max–min–max–min structure, we develop a backward-analysis-based solution method and an exact branch-check-and-Benders-cut algorithm enhanced by tailored acceleration techniques. Experiments on real-world instances demonstrate the algorithm’s efficiency and superiority.