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Ridesharing Problem with Flexible Pickup and Delivery Locations for App-Based Transportation Service: Mathematical Modeling and Decomposition Methods

机译:基于应用程序的运输服务具有灵活取货和送货地点的拼车问题:数学建模和分解方法

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App-based transportation service system, such as Uber and Didi, has brought a new transportation mode to users, who are able to make reservations using mobile apps conveniently. However, one of the fundamental challenges in app-based transportation system is the inefficiency and unreliability of the vehicle routing plans caused by complex topology of urban road network and unpredictable traffic conditions. A common way to tackle this problem is repositioning pickup or delivery locations via the coordination between drivers and passengers. This paper studies an on-demand ridesharing problem that determines the optimal ride-share matching strategy and vehicle routing plan with respect to flexible pickup and delivery locations. By introducing the concept of space-time windows, the problem is formulated as the pickup and delivery problem with space-time windows (PDPSW) in space-time network. To solve the model efficiently and accurately, we particularly develop a customized solution approach based on Lagrangian relaxation. Numerical examples are conducted to demonstrate the performance of the proposed framework and draw some managerial insights into the optimal system operation. The results indicate that adopting the serving strategy of flexible pickup and delivery locations will evidently reduce the system cost and improve the service quality in app-based transportation service systems.
机译:诸如Uber和Didi之类的基于应用程序的运输服务系统为用户带来了一种新的运输模式,使他们能够方便地使用移动应用程序进行预订。然而,基于应用程序的运输系统的基本挑战之一是由于城市道路网络的复杂拓扑结构和不可预测的交通状况而导致的车辆路线规划效率低下和不可靠。解决此问题的常用方法是通过驾驶员和乘客之间的协调来重新定位接送位置。本文研究了按需乘车共享问题,该问题确定了关于灵活的收货和送货地点的最佳乘车份额匹配策略和车辆路线计划。通过引入时空窗口的概念,将该问题表述为时空网络中带有时空窗口(PDPSW)的收货和交付问题。为了有效,准确地求解模型,我们特别开发了基于拉格朗日松弛的定制解决方案。进行了数值算例,以证明所提出框架的性能,并从管理角度对最佳系统操作进行了分析。结果表明,采用灵活的收货和送货地点服务策略将明显降低系统成本,提高基于应用程序的运输服务系统的服务质量。

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