讲座：Robust Pricing and Production with Information Partitioning and Adaptation
题 目：Robust Pricing and Production with Information Partitioning and Adaptation
演讲人：汤勤深 助理教授 新加坡南洋理工大学
主持人：李成璋 助理教授 上海交通大学安泰经济与管理学院
In this paper, we introduce a new distributionally robust optimization model to address a two-period, multi-item joint pricing and production problem, which can be implemented in a data-driven setting using historical demand and side information pertinent to the prediction of demands. Starting from an additive demand model we introduce a new partitioned-moment-based ambiguity set to characterize its residuals and investigate the joint pricing and production problem by proposing a cluster-adapted markdown policy and an affine recourse approximation, which allows us to reformulate the problem as a mixed-integer linear optimization problem that we can solve to optimality using commercial solvers. Both the case study and our simulation study demonstrate that, with only a few number of clusters, the cluster-adapted markdown policy and ambiguity set can improve mean profit over the empirical model---when applied to most out-of-sample tests.
Dr. Tang Qinshen is an assistant professor at the Nanyang Business School, Nanyang Technological University. Before joining NBS, he was a research fellow at the Institute of Operations Research and Analytics, National University of Singapore. He received his Ph.D. in Analytics and Operations from the National University of Singapore, and his M.S. in Management Science and Engineering, B.S. in Industrial Engineering from South China University of Technology. His primary research interests lie in data-driven and target-based decision making under uncertainty, with applications in operations and supply chain management. He is also interested in applying cooperative and non-cooperative game theory in solving problems in the interface of operations management and marketing/economics.