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一种用于带容量限制的电动车辆路径规划问题的双层蚁群优化算法。

A Bilevel Ant Colony Optimization Algorithm for Capacitated Electric Vehicle Routing Problem.

作者信息

Jia Ya-Hui, Mei Yi, Zhang Mengjie

出版信息

IEEE Trans Cybern. 2022 Oct;52(10):10855-10868. doi: 10.1109/TCYB.2021.3069942. Epub 2022 Sep 19.

Abstract

The development of electric vehicle (EV) techniques has led to a new vehicle routing problem (VRP) called the capacitated EV routing problem (CEVRP). Because of the limited number of charging stations and the limited cruising range of EVs, not only the service order of customers but also the recharging schedules of EVs should be considered. However, solving these two aspects of the problem together is very difficult. To address the above issue, we treat CEVRP as a bilevel optimization problem and propose a novel bilevel ant colony optimization algorithm in this article, which divides CEVRP into two levels of subproblem: 1) capacitated VRP and 2) fixed route vehicle charging problem. For the upper level subproblem, the electricity constraint is ignored and an order-first split-second max-min ant system algorithm is designed to generate routes that fulfill the demands of customers. For the lower level subproblem, a new effective heuristic is designed to decide the charging schedule in the generated routes to satisfy the electricity constraint. The objective values of the resultant solutions are used to update the pheromone information for the ant system algorithm in the upper level. Through good orchestration of the two components, the proposed algorithm can significantly outperform state-of-the-art algorithms on a wide range of benchmark instances.

摘要

电动汽车(EV)技术的发展引发了一种新的车辆路径规划问题(VRP),即容量受限电动汽车路径规划问题(CEVRP)。由于充电站数量有限以及电动汽车续航里程受限,不仅要考虑客户的服务顺序,还应考虑电动汽车的充电计划。然而,同时解决这两个方面的问题非常困难。为了解决上述问题,本文将CEVRP视为一个双层优化问题,并提出了一种新颖的双层蚁群优化算法,该算法将CEVRP分为两个层次的子问题:1)容量受限VRP和2)固定路线车辆充电问题。对于上层子问题,忽略电力约束,设计了一种订单优先分秒最大最小蚁群系统算法来生成满足客户需求的路线。对于下层子问题,设计了一种新的有效启发式算法来确定生成路线中的充电计划,以满足电力约束。所得解的目标值用于更新上层蚁群系统算法的信息素信息。通过对这两个组件的良好编排,所提出的算法在广泛的基准实例上能够显著优于现有算法。

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