Optimised crossover genetic algorithm for capacitated vehicle routing problem

This paper presents a genetic algorithm for solving capacitated vehicle routing problem, which is mainly characterised by using vehicles of the same capacity based at a central depot that will be optimally routed to supply customers with known demands. The proposed algorithm uses an optimised crosso...

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Main Authors: Nazif, Habibeh, Lee, Lai Soon
Format: Article
Language:English
Published: Elsevier 2012
Online Access:http://psasir.upm.edu.my/id/eprint/25245/1/Optimised%20crossover%20genetic%20algorithm%20for%20capacitated%20vehicle%20routing%20problem.pdf
http://psasir.upm.edu.my/id/eprint/25245/
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spelling my.upm.eprints.252452018-01-16T08:59:39Z http://psasir.upm.edu.my/id/eprint/25245/ Optimised crossover genetic algorithm for capacitated vehicle routing problem Nazif, Habibeh Lee, Lai Soon This paper presents a genetic algorithm for solving capacitated vehicle routing problem, which is mainly characterised by using vehicles of the same capacity based at a central depot that will be optimally routed to supply customers with known demands. The proposed algorithm uses an optimised crossover operator designed by a complete undirected bipartite graph to find an optimal set of delivery routes satisfying the requirements and giving minimal total cost. We tested our algorithm with benchmark instances and compared it with some other heuristics in the literature. Computational results showed that the proposed algorithm is competitive in terms of the quality of the solutions found. Elsevier 2012-05 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/25245/1/Optimised%20crossover%20genetic%20algorithm%20for%20capacitated%20vehicle%20routing%20problem.pdf Nazif, Habibeh and Lee, Lai Soon (2012) Optimised crossover genetic algorithm for capacitated vehicle routing problem. Applied Mathematical Modelling, 36 (5). pp. 2110-2117. ISSN 0307-904X; ESSN: 1872-8480 10.1016/j.apm.2011.08.010
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description This paper presents a genetic algorithm for solving capacitated vehicle routing problem, which is mainly characterised by using vehicles of the same capacity based at a central depot that will be optimally routed to supply customers with known demands. The proposed algorithm uses an optimised crossover operator designed by a complete undirected bipartite graph to find an optimal set of delivery routes satisfying the requirements and giving minimal total cost. We tested our algorithm with benchmark instances and compared it with some other heuristics in the literature. Computational results showed that the proposed algorithm is competitive in terms of the quality of the solutions found.
format Article
author Nazif, Habibeh
Lee, Lai Soon
spellingShingle Nazif, Habibeh
Lee, Lai Soon
Optimised crossover genetic algorithm for capacitated vehicle routing problem
author_facet Nazif, Habibeh
Lee, Lai Soon
author_sort Nazif, Habibeh
title Optimised crossover genetic algorithm for capacitated vehicle routing problem
title_short Optimised crossover genetic algorithm for capacitated vehicle routing problem
title_full Optimised crossover genetic algorithm for capacitated vehicle routing problem
title_fullStr Optimised crossover genetic algorithm for capacitated vehicle routing problem
title_full_unstemmed Optimised crossover genetic algorithm for capacitated vehicle routing problem
title_sort optimised crossover genetic algorithm for capacitated vehicle routing problem
publisher Elsevier
publishDate 2012
url http://psasir.upm.edu.my/id/eprint/25245/1/Optimised%20crossover%20genetic%20algorithm%20for%20capacitated%20vehicle%20routing%20problem.pdf
http://psasir.upm.edu.my/id/eprint/25245/
_version_ 1643828602841595904
score 13.160551