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首页> 外文期刊>Transportation Research Part B: Methodological >Multiple depot vehicle scheduling with controlled trip shifting
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Multiple depot vehicle scheduling with controlled trip shifting

机译:带有可控行程切换的多站点车辆调度

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摘要

The multiple depot vehicle scheduling problem (MDVSP) has been widely studied in the context of public transit systems. Given a timetable of bus trips, it consists of finding a set of bus schedules that covers every trip exactly once while satisfying vehicle availability at each depot and minimizing the operating costs. This work considers a generalization of the MDVSP that allows slight modifications of the trip scheduled start times. By shifting some trips, one can indeed expect to cover all trips with fewer vehicles or less expensive deadheads (vehicle moves without passengers). However, reducing the operational costs in this way should not be too detrimental to the overall quality of the timetable and, therefore, the following criteria should be controlled: the number of shifted trips, the headways between the consecutive trips of a line, and the quality of some passenger connections. To solve this generalized problem, we develop a two-phase matheuristic: the first phase computes vehicle schedules with a column-generation heuristic: the second relies on a mixed integer program to find the best possible timetable considering the computed vehicle schedules. Penalties are introduced in the first phase to increase the chances of finding a better-quality timetable in the second phase. Computational tests on real-life datasets from a bus company show that the proposed matheuristic can solve the problem efficiently, yielding solutions with a significant reduction in the number of vehicles used compared to the solutions of the classical MDVSP and a limited alteration of the timetable. (C) 2018 Elsevier Ltd. All rights reserved.
机译:在公共交通系统的背景下,已经广泛研究了多仓库车辆调度问题(MDVSP)。给定公交车旅行的时间表,它包括找到一组公交车时间表,该时间表准确地覆盖每次旅行,同时满足每个仓库的车辆可用性,并最大程度地降低运营成本。这项工作考虑了MDVSP的一般化,它允许对行程计划的开始时间进行一些修改。通过改变某些行程,确实可以期望以更少的车辆或更便宜的死角覆盖所有行程(无乘客的车辆行驶)。但是,以这种方式降低运营成本不应对时间表的整体质量造成太大的损害,因此,应控制以下标准:转移行程,线路连续两次行程之间的行进距离以及一些乘客连接的质量。为了解决这个普遍的问题,我们开发了一个两阶段的数学方法:第一阶段使用列生成启发式算法来计算车辆时间表:第二阶段依靠混合整数程序来考虑计算的车辆时间表来找到最佳的时间表。在第一阶段引入了惩罚措施,以增加在第二阶段中找到质量更高的时间表的机会。对一家公交公司的真实数据集进行的计算测试表明,所提出的数学方法可以有效地解决该问题,与传统的MDVSP的解决方案相比,所使用的车辆数量大大减少,并且时间表变更有限,从而产生了解决方案。 (C)2018 Elsevier Ltd.保留所有权利。

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