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

机译:基于应用的运输服务的灵活拾取和交付位置的ridesharing问题:数学建模和分解方法

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摘要

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:基于应用的运输服务系统,如优步和DIDI,为用户带来了新的交通模式,他们能够方便地使用移动应用程序进行预订。然而,基于应用的运输系统的基本挑战之一是由城市道路网络复杂拓扑和不可预测的交通状况引起的车辆路线计划的效率低下。解决此问题的常见方法是通过驱动程序和乘客之间的协调重新定位拾取或交付位置。本文研究了一个按需骑行问题,确定了灵活拾取和交付位置的最佳乘坐匹配策略和车辆路由计划。通过介绍时空窗口的概念,将问题作为时空网络中的时空窗口(PDPSW)作为拾取和交付问题。为了有效准确地解决模型,我们特别开发了一种基于拉格朗日放松的定制解决方案方法。进行数值示例以展示所提出的框架的性能,并将一些管理洞察力扩展到最佳系统操作中。结果表明,采用灵活拾取和交付位置的服务策略将显着降低系统成本,提高基于应用的运输服务系统中的服务质量。

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