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A 3-step math heuristic for the static repositioning problem in bike-sharing systems

机译:针对共享单车系统中静态重新定位问题的三步数学启发式方法

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Over the last few years, bike-sharing systems have emerged as a new mode of transportation in a large number of big cities worldwide. This new type of mobility mode is still developing, and many challenges associated with its operation are not well addressed yet. One such major challenge of bike-sharing systems is the need to respond to fluctuating demands for bicycles and for vacant lockers at each station, which directly influences the service level provided to its users. This is done using dedicated repositioning vehicles (light trucks) that are routed through the stations, loading and unloading bicycles to/from them. Performing this operation during the night when the demand in the system is negligible is referred to as the static repositioning problem. In this paper, we propose a 3-step mathematical programming based heuristic for the static repositioning problem. In the first step, stations are clustered according to geographic as well as inventory (of bicycles) considerations. In the second step the repositioning vehicles are routed through the clusters while tentative inventory decisions are made for each individual station. Finally, the original repositioning problem is solved with the restriction that traversal of the repositioning vehicles is allowed only between stations that belong to consecutive clusters according to the routes determined in the previous step, or between stations of the same cluster. In the first step the clusters are formed using a specialized saving heuristic. The last two steps are formulated as Mixed Integer Linear Programs and solved by a commercial solver. The method was tested on instances of up to 200 stations and three repositioning vehicles, and was shown to outperform a previous method suggested in the literature for the same problem. (C) 2014 Elsevier Ltd. All rights reserved.
机译:在过去的几年中,自行车共享系统已成为世界上许多大城市的一种新型交通方式。这种新型的出行方式仍在发展中,与其操作相关的许多挑战尚未得到很好的解决。自行车共享系统的这种主要挑战之一是需要对每个站点对自行车和空置储物柜的变动需求做出响应,这直接影响了提供给其用户的服务水平。这是通过专用的重新定位车辆(轻型卡车)来完成的,这些车辆通过车站行驶,将自行车装卸到车站或从车站卸下自行车。在系统需求微不足道的夜晚执行此操作称为静态重新定位问题。在本文中,我们针对静态重定位问题提出了一种基于启发式的三步数学编程方法。第一步,根据地理位置和(自行车的)存货因素对车站进行聚类。在第二步中,将重新定位的车辆引导通过集群,同时为每个单独的站点做出临时的库存决策。最后,原始的重新定位问题受到以下限制的解决:仅根据上一步中确定的路线,仅允许在属于连续集群的站点之间或在同一集群的站点之间遍历重新定位车辆。第一步,使用专门的保存启发式方法形成聚类。最后两个步骤被公式化为混合整数线性程序,并由商业求解器求解。该方法已在多达200个工位和三辆重新定位车辆的实例上进行了测试,结果表明其性能优于文献中针对相同问题提出的方法。 (C)2014 Elsevier Ltd.保留所有权利。

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