一种改进的混合遗传算法来解决有顶点数限制的多车辆覆盖漫游问题

Manel Kammoun
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引用次数: 0

摘要

在本文中,我们解决了仅对每条路线的顶点数(m-CTP-p)进行限制的多车辆覆盖漫游问题。m-CTP的目标是尽量减少总路线成本,并满足所有客户的需求,这样,任何路线都不能覆盖到每个客户。每个被覆盖的顶点必须在至少一个访问顶点的给定距离内,并且路线上的顶点数量不超过预定义的数字p。我们提出了两种方法来解决这种变体。首先,我们开发了一个使用迭代改进机制的遗传算法(GA)。然后,在基于变量邻域下降法的局部搜索启发式算法的基础上,提出了一种有效的混合遗传算法(HGA)来改进解。基于m-CTP-p问题的基准实例的大量计算结果表明了我们的方法的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An improved hybrid genetic algorithm to solve the multi-vehicle covering tour problem with restriction on the number of vertices
In this paper, we address the multi-vehicle covering tour problem where only the restriction on the number of vertices in each route (m-CTP-p). The objective of the m-CTP is to minimise the total routing cost and fulfill the demand of all customers such that each customer which is not included in any route must be covered. Each covered vertex must be within a given distance of at least a visited vertex and the number of vertices on a route does not exceed a pre-defined number p. We propose two approaches to solve this variant. First, we develop a genetic algorithm (GA) using an iterative improvement mechanism. Then, an effective hybrid genetic algorithm (HGA) is developed in addition to a local search heuristic based on variable neighborhood descent method to improve the solution. Extensive computational results based on benchmark instances on the m-CTP-p problem show the performance of our methods.
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