拼车服务中的汽车搬迁:CPLEX与贪心搜索的比较

2014 IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems (CIVTS) Pub Date : 2014-12-01 DOI:10.1109/CIVTS.2014.7009477

Rabih Zakaria, M. Dib, L. Moalic, A. Caminada

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引用次数: 14

摘要

本文提出了两种解决单向汽车共享系统中车辆迁移问题的方法。我们首先将问题表述为一个整数线性规划模型。然后，使用从运营汽车共享系统收集的移动数据，我们构建了需求矩阵，这些矩阵将用作求解器的输入数据。我们注意到，当我们增加参与重新安置过程的员工数量以及当系统变得更大时，使用精确求解器解决ILP所需的时间会急剧增加。为了解决这个问题，我们开发了一种贪心算法，以便在更快的时间内解决重定位问题。在最坏的情况下，我们的算法只需1秒即可解决重定位问题;此外，我们使用不同员工数量的随机输入数据来评估这两种方法的稳健性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Car relocation for carsharing service: Comparison of CPLEX and greedy search

In this paper, we present two approaches to solve the relocation problem in one-way carsharing system. We start by formulating the problem as an Integer Linear Programming Model. Then using mobility data collected from an operational carsharing system, we built demands matrices that will be used as input data for our solver. We notice that the time needed to solve the ILP using an exact solver increases dramatically when we increase the number of employees involved in the relocation process and when the system gets bigger. To cope with this problem, we develop a greedy algorithm in order to solve the relocation problem in a faster time. Our algorithm takes one second to solve the relocation problem in worst cases; also, we evaluated the robustness of the two approaches with stochastic input data using different numbers of employees.

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2014 IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems (CIVTS)

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