报告题目： Finite-Horizon Approximate Linear Programs for an Infinite-Horizon Revenue Management Problem

报 告 人：Dan Zhang

报告时间：2018年5月28日（星期一）上午9:30-11:30

报告地点：老校部二楼大会议室

邀 请 人：工业与系统工程研究所 唐立新教授

Abstract: Approximate linear programs have been widely used to approximately solve stochastic dynamic programs that suffer from the curse of dimensionality. Due to the canonical results establishing the optimality of stationary value functions and policies for infinite-horizon dynamic programs, the literature has focused on approximation architectures that are stationary over time. We consider finite-horizon approximations where the parameters are time-dependent within a pre-determined time horizon and are stationary afterwards. Such finite-horizon approximations were widely used in the theoretical analysis of infinite-horizon stochastic dynamic programs, but have not been considered in the approximate linear programming literature. We apply this approach with an affine approximation architecture to a rolling-horizon revenue management problem. We obtain two main results. First, it leads to an upper bound on the optimal revenue, which becomes successively stronger as the horizon length increases. Second, the resulting approximate linear programs admit compact representations and therefore can be efficiently solved. In numerical experiments, finite-horizon approximations with appropriately chosen horizon length dramatically reduce the gap between the optimal value and the commonly used stationary approximation.

Resume：Dan Zhang is Associate Professor of Management and Entrepreneurship at Leeds School of Business, University of Colorado Boulder. Prior to Leeds, he was an assistant professor of operations management at Desautels Faculty of Management, McGill University in Montreal, Canada. Dr. Zhang received his PhD in industrial engineering from University of Minnesota and subsequently did postdoctoral work at Booth School of Business, University of Chicago. His current primary research interest is revenue management and pricing. Dr. Zhang is a frequent reviewer for academic journals, conferences, and grant agencies. Dr. Zhang currently serves on the editorial board of Journal of Revenue and Pricing Management, and is a Senior Editor for the journal Production and Operations Management. Dr. Zhang teaches in the area of operations management and data analytics.