An improved hybrid firefly algorithm for capacitated vehicle routing problem
An improved hybrid firefly algorithm for capacitated vehicle routing problem
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DOI：
10.1016/j.asoc.2019.105728
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发表时间：
2019-11-01
影响因子：
8.7
通讯作者：
Ghallab, Abdullatif
中科院分区：
文献类型：
--
作者：
Altabeeb, Asma M.;Mohsen, Abdulqader M.;Ghallab, Abdullatif
萤火虫算法（FA）是一种新的元启发式算法，已成功地应用于解决多个优化问题。然而，它有一个缺点，容易陷入局部最优。本文提出了一种新的混合FA，称为CVRP-FA，解决能力约束的车辆路径问题。在CVRP-FA中，FA与两种类型的局部搜索和遗传算子相结合，以提高解的质量和加速收敛。在82个基准实例上进行了实验。结果表明，CVRP-FA具有收敛速度快，计算精度高。在大多数测试实例中，它显著优于其他最先进的FA变体。(C)2019爱思唯尔B. V.保留所有权利。
Firefly algorithm (FA) is a new meta-heuristic which is successfully applied to solve several optimization problems. However, it suffers from a drawback of easily getting stuck at local optima. This paper proposes a new hybrid FA, called CVRP-FA, to solve capacitated vehicle routing problem. In CVRP-FA, FA is integrated with two types of local search and genetic operators to enhance the solution's quality and accelerate the convergence. The experiments are conducted over 82 benchmark instances. The results demonstrate that CVRP-FA has fast convergence rate and high computational accuracy. It significantly outperforms the other state-of-the-art FA variants in majority of the tested instances. (C) 2019 Elsevier B.V. All rights reserved.