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An improved fireworks algorithm for the capacitated vehicle routing problem

机译:车辆容量不足问题的改进烟花算法

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The capacitated vehicle routing problem (CVRP), which aims at minimizing travel costs, is a well-known NP-hard combinatorial optimization. Owing to its hardness, many heuristic search algorithms have been proposed to tackle this problem. This paper explores a recently proposed heuristic algorithm named the fireworks algorithm (FWA), which is a swarm intelligence algorithm. We adopt FWA for the combinatorial CVRP problem with several modifications of the original FWA: it employs a new method to generate sparks according to the selection rule, and it uses a new method to determine the explosion amplitude for each firework. The proposed algorithm is compared with several heuristic search methods on some classical benchmark CVRP instances. The experimental results show a promising performance of the proposed method. We also discuss the strengths and weaknesses of our algorithm in contrast to traditional algorithms.
机译:旨在使出行成本最小化的车辆限行问题(CVRP)是众所周知的NP-hard组合优化。由于其硬度,已经提出了许多启发式搜索算法来解决该问题。本文探讨了最近提出的启发式算法,称为烟火算法(FWA),这是一种群体智能算法。我们对组合CVRP问题采用FWA,并对原始FWA进行了几处修改:它采用了一种新的方法根据选择规则生成火花,并使用一种新的方法来确定每个烟花的爆炸幅度。将该算法与一些经典基准CVRP实例上的几种启发式搜索方法进行了比较。实验结果表明该方法具有良好的性能。与传统算法相比,我们还讨论了我们算法的优点和缺点。

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