Conflict-free electric vehicle routing problem: an improved compositional algorithm

Sabino Francesco Roselli, Martin Fabian, Knut Åkesson
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Abstract

The Conflict-Free Electric Vehicle Routing Problem (CF-EVRP) is a combinatorial optimization problem of designing routes for vehicles to execute tasks such that a cost function, typically the number of vehicles or the total travelled distance, is minimized. The CF-EVRP involves constraints such as time windows on the tasks’ execution, limited operating range of the vehicles, and limited capacity on the number of vehicles that a road segment can simultaneously accommodate. In previous work, the compositional algorithm ComSat was introduced to solve the CF-EVRP by breaking it down into sub-problems and iteratively solve them to build an overall solution. Though ComSat showed good performance in general, some problem instances took significant time to solve due to the high number of iterations required to find solutions for two sub-problems, namely the Routing Problem, and the Paths Changing Problem. This paper addresses the bottlenecks of ComSat and presents new formulations for both sub-problems in order to reduce the number of iterations required to find feasible solutions to the CF-EVRP. Experiments on sets of benchmark instances show the effectiveness of the presented improvements.

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无冲突电动汽车路由问题:一种改进的组合算法
无冲突电动汽车路由问题(CF-EVRP)是一个组合优化问题,即设计车辆执行任务的路线,使成本函数(通常是车辆数量或总行驶距离)最小化。CF-EVRP 涉及的约束条件包括任务执行的时间窗口、车辆的有限运行范围以及路段可同时容纳车辆数量的有限容量。在之前的工作中,ComSat 算法被用来解决 CF-EVRP 问题,该算法将 CF-EVRP 分解为多个子问题,并通过迭代解决这些子问题来建立整体解决方案。虽然 ComSat 总体表现良好,但由于路由问题和路径改变问题这两个子问题的求解需要大量迭代,因此某些问题实例的求解耗费了大量时间。本文针对 ComSat 的瓶颈问题,提出了这两个子问题的新公式,以减少找到 CF-EVRP 可行解所需的迭代次数。在一组基准实例上进行的实验表明了所提出的改进措施的有效性。
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