Solving capacitated vehicle routing problem using cooperative firefly algorithm

被引:59
|
作者
Altabeeb, Asma M. [1 ]
Mohsen, Abdulqader M. [1 ,2 ]
Abualigah, Laith [3 ]
Ghallab, Abdullatif [1 ]
机构
[1] Univ Sci & Technol, Fac Comp & Informat Technol, Sanaa, Yemen
[2] Univ Aden, Fac Comp & Informat Technol, Aden, Yemen
[3] Amman Arab Univ, Fac Comp Sci & Informat, Amman, Jordan
关键词
Discrete firefly algorithm; Parallel firefly algorithm; Parallel metaheuristics; Local search; Hybrid firefly algorithm; NEIGHBORHOOD SEARCH ALGORITHM; OPTIMIZATION;
D O I
10.1016/j.asoc.2021.107403
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The capacitated vehicle routing problem (CVRP) is a classical combinatorial optimization problem, which has received much attention due to its main challenges as distribution, logistics, and transportation. This proposed attempts to find the vehicle routes with minimizing traveling distance, in which the excellent solution delivers a set of customers in one visit by capacitated vehicle. For solving the CVRP problem, a cooperative hybrid firefly algorithm (CVRP-CHFA) is proposed in this paper with multiple firefly algorithm (FA) populations. Each FA is hybridized with two types of local search (i.e., Improved 2-opt as a local search and 2-h-opt as a mutation operator) and genetic operators. The proposed algorithms (FAs) communicate from time to time for exchanging some solutions (fireflies). The main aim of the hybridization and communication strategies is to maintain the diversity of populations to prevent the proposed algorithm from falling into local optima and overcome the drawbacks of a single swarm FA. The experiments are conducted on 108 instances from eight standard benchmarks. The results revealed that the proposed CVRP-CHFA got promising results compared to other well-known methods. Moreover, the proposed CVRP-CHFA significantly outperformed the recent three hybrid firefly algorithms. (C) 2021 Elsevier B.V. All rights reserved.
引用
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页数:20
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