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首页> 外文期刊>International journal of applied evolutionary computation >Efficient Golden-Ball Algorithm Based Clustering to solve the Multi- Depot VRP With Time Windows
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Efficient Golden-Ball Algorithm Based Clustering to solve the Multi- Depot VRP With Time Windows

机译:基于高效金球算法的聚类算法,解决带时间窗的多仓库VRP

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摘要

In this article, the authors propose a decision support system which aims to optimize the classical Capacitated Vehicle Routing Problem by considering the existence of multiple available depots and a time window which must not be violated, that they call the Multi-Depot Vehicle Routing Problem with Time Window (MDVRPTW), and with respecting a set of criteria including: schedules requests from clients, the capacity of vehicles. The authors solve this problem by proposing a recently published technique based on soccer concepts, called Golden Ball (GB), with different solution representation from the original one, this technique was designed to solve combinatorial optimization problems, and by embedding a clustering algorithm. Computational results have shown that the approach produces acceptable quality solutions compared to the best previous results in similar problem in terms of generated solutions and processing time. Experimental results prove that the proposed Golden Ball algorithm is efficient and effective to solve the MDVRPTW problem.
机译:在本文中,作者提出了一个决策支持系统,旨在通过考虑存在多个可用仓库和一个不应该违反的时间窗来优化经典的“容量限制车辆路径问题”,他们称其为“多站点车辆路径问题”。时间窗口(MDVRPTW),并遵守一系列标准,包括:安排客户的要求,车辆的容量。作者通过提出一种基于足球概念的最新发布的技术来解决此问题,该技术被称为Golden Ball(GB),与原始技术的解决方案表示形式有所不同,该技术旨在解决组合优化问题,并嵌入了聚类算法。计算结果表明,与在类似问题上产生的解决方案和处理时间方面的最佳先前结果相比,该方法可产生可接受的质量解决方案。实验结果证明,提出的Golden Ball算法是解决MDVRPTW问题的有效方法。

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