Operating Policies With Temporally and Spatially Varied Parameters in Station-Based Carsharing Services
研究了站点式汽车共享服务中两种运营策略（自由预约和额外停车），提出时空变化参数方案以最大化利润，并通过仿真优化验证其有效性，相比统一参数方案利润提升约20%。
This study investigates two operating policies with temporally and spatially varied parameters in station-based carsharing services, which are becoming a popular traffic mode. One is the so-called free-reservation policy, in which a user can reserve a car freely before his/her trip. The other is the extra-parking policy, in which a user can return a car to a station without valid parking slots but with a fixed extra-parking fee paid. A scheme with temporally and spatially varied parameters is proposed to maximize the total operational profit, where key service parameters in the two policies are varied with stations and periods. The strategic behavior of users is considered which involves the choices of both transportation modes and carsharing stations. A simulation-based optimization solution method is developed to optimize the key parameters in the policies, where the solution space is reduced. Extensive numerical experiments validate the solution method and the scheme with varied parameters. The results indicate that the scheme with varied parameters increases the total profit by approximately 20% compared to the scheme with unified parameters in the configuration of experiments. Several managerial implications are also proposed to help carsharing platforms utilize resources efficiently.