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讲座:On-Demand Ride-Matching in a Spatial Model with Abandonment and Cancellation

发布者:人力资源办公室    发布时间:2019-09-27

管理科学系学术讲座

 目:On-Demand Ride-Matching in a Spatial Model with Abandonment and Cancellation

演讲人:张海伦 助理教授 香港中文大学(深圳)

主持人:宋颖达 助理教授 上海交通大学安泰经济与管理学院

时 间:2019年10月9日(周三)10:00-11:30

地 点:上海交通大学徐汇校区 安泰楼A305室

 

Abstract:

    Ride-hailing platforms such as Uber, Lyft, and DiDi coordinate supply and demand by matching passengers and drivers. The platform has to promptly dispatch drivers when receiving requests, since otherwise passengers may lose patience and abandon the service by switching to alternative transportation methods.  However, having less idle drivers results in a possible lengthy pick-up time, which is a waste of system capacity and may cause passengers to cancel the service after they are matched.  Due to complex spatial and queueing dynamics, the analysis of the matching decision is challenging. In this paper, we propose a spatial model to approximate the pick-up time based on the number of waiting passengers and idle drivers.  We analyze the dynamics of passengers and drivers in a queueing model where the platform can control the matching process by setting a threshold on the expected pick-up time. Applying fluid approximations, we obtain accurate performance evaluations and an elegant optimality condition, based on which we propose a policy that adapts to time-varying demand.

 

Bio:

    Dr. Hailun Zhang is an assistant professor in Institute for Data and Decision Analytics (iDDA), The Chinese University of Hong Kong, Shenzhen. Before joining CUHKSZ, he is a Postdoc fellow in Department of Industrial Engineering and Decision Analytics at HKUST, where he obtained a Ph.D. degree in July 2018. His research interests lie in dynamic matching in queuing networks, online algorithm design and supply chain management. Before HKUST, he received his bachelor and master's degree in Mathematics department from Peking University. He is from Hubei, China.


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