Optimizing the Profitability and Quality of Service in Carshare Systems Under Demand Uncertainty
Optimizing the Profitability and Quality of Service in Carshare Systems Under Demand Uncertainty
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DOI：
10.1287/msom.2017.0644
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发表时间：
2018-03-01
影响因子：
6.3
通讯作者：
Shen, Siqian
中科院分区：
文献类型：
--
作者：
Lu, Mengshi;Chen, Zhihao;Shen, Siqian
汽车共享被认为是增加机动性和减少个人车辆使用及相关碳排放的有效手段。在本文中，我们考虑的问题，分配汽车共享车队的服务区下不确定的单程和往返租赁需求。我们采用了两阶段随机整数规划模型，在第一阶段，我们分配共享车队和购买停车场或许可证的预约或自由浮动系统。在第二阶段，我们生成一组有限的样本来表示需求的不确定性，并为每个样本构建一个时空网络来模拟车辆运动和相应的租金收入，运营成本和未满足需求的罚款。我们最小化预期的总成本减去利润和开发的分支和切割算法与混合整数，舍入增强Benders削减，这可以显着提高计算效率时，在并行计算中实现。我们将我们的模型应用于Zipcar在马萨诸塞州波士顿-剑桥地区的数据集，以证明我们的方法的有效性，并对汽车共享管理提出见解。研究结果表明，在给定单程和往返价差和车辆搬迁成本的情况下，外生单向需求可以增加汽车共享的盈利能力，而由于定价和战略客户行为而内生产生的单向需求可能会降低汽车共享的盈利能力。我们的模型也可以应用于滚动框架，以提供优化的车辆重新定位决策，并实现直观的车队再平衡政策的显着改善。
Carsharing has been considered as an effective means to increase mobility and 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, in the first stage of which we allocate shared vehicle fleet and purchase parking lots or permits in reservation-based or free-floating 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-enhanced Benders cuts, which can significantly improve computation efficiency when implemented in parallel computing. We apply our model to a data set of Zipcar in the Boston-Cambridge, Massachusetts, area 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 given one-way and round-trip price differences and vehicle relocation cost whereas endogenously generated one-way demand as a result of pricing and strategic customer behavior may decrease carshare profitability. Our model can also be applied in a rolling-horizon framework to deliver optimized vehicle relocation decisions and achieve significant improvement over an intuitive fleet-rebalancing policy.