题目：Optimizing the Profitability and Quality of Service in Carshare Systems under Demand Uncertainty
主讲人：吕梦石 助理教授（普度大学）
时间：2016年12月21日 9:30-10:15
地点：主楼216
主讲人介绍：
Mengshi Lu is an Assistant Professor at the Krannert Graduate School of Management, Purdue University. His current research interests are prescriptive analytics and operations management of innovative systems. He received his Ph.D. in Industrial Engineering and Operations Research from UC Berkeley in 2014. He has published on MSOM、Transportation Research Part B、NRL、IJPR，etc..
内容介绍：
Carsharing has been considered as an effective means to increase mobility, reduce personal vehicle usage and related carbon emissions. In this paper, we consider problems of allocating a carshare fleet to service zones under uncertain one-way and round-trip rental demand. We employ a two-stage stochastic integer programming model, where in the first stage, we allocate shared vehicle fleet and purchase parking lots or permits in reservation-based or free-float systems. In the second stage, we generate a finite set of samples to represent demand uncertainty and construct a spatial-temporal network for each sample to model vehicle movement and the corresponding rental revenue, operating cost, and penalties from unserved demand. We minimize the expected total costs minus profit, and develop branch-and-cut algorithms with mixed-integer rounding (MIR)-enhanced Benders cuts, which can significantly improve computation efficiency when implemented in parallel. We apply our model to a data set of Zipcar in Boston to demonstrate the efficacy of our approaches and draw insights on carshare management. Our results show that exogenously given one-way demand can increase carshare profitability under the current price difference and vehicle relocation cost, whereas endogenously generated one-way demand as a result of pricing and strategic customer behavior may decrease carshare profitability. Joint work with Siqian Shen and Zhihao Chen (University of Michigan)
（承办：管理科学与物流系，科研与学术交流中心）
