学术前沿讲座——Supermodularity in Two-Stage Distributionally Robust Optimization --- Theory and Applications
Supermodularity in Two-Stage Distributionally Robust Optimization --- Theory and Applications
Driven by several classic operations management problems (e.g., appointment scheduling), we solve a class of two-stage distributionally robust optimization problems which have the property of supermodularity. We exploit the explicit upper bounds on the expectation of supermodular functions and derive the worst-case distribution for the robust counterpart. This enables us to develop an efficient method to derive an exact optimal solution of these two-stage problems. Further, we provide a necessary and sufficient condition to check whether any given two-stage optimization problem has supermodularity. We apply this framework to classic problems, including the multi-item newsvendor problem, the appointment scheduling problem and general assemble-to-order (ATO) systems. While these problems are typically computationally challenging, they can be solved efficiently using our approach.
Zhuoyu Long is an associate professor in the Department of Systems Engineering & Engineering Management at The Chinese University of Hong Kong. He earned his PhD in the Department of Analytics and Operation, National University of Singapore in 2013. Before that, Long received his bachelor degree from Tsinghua University, and master degree from Chinese Academy of Science. His research interests are in inventory control, project management, risk management, and robust optimization.