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/
http://psasir.upm.edu.my/id/eprint/25245/1/Optimised%20crossover%20genetic%20algorithm%20for%20capacitated%20vehicle%20routing%20problem.pdf
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author Nazif, Habibeh
Lee, Lai Soon
author_facet Nazif, Habibeh
Lee, Lai Soon
author_sort Nazif, Habibeh
building UPM Institutional Repository
collection Online Access
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.
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institution Universiti Putra Malaysia
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spelling upm-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
spellingShingle Nazif, Habibeh
Lee, Lai Soon
Optimised crossover genetic algorithm for capacitated vehicle routing problem
title 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_short Optimised crossover genetic algorithm for capacitated vehicle routing problem
title_sort optimised crossover genetic algorithm for capacitated vehicle routing problem
url http://psasir.upm.edu.my/id/eprint/25245/
http://psasir.upm.edu.my/id/eprint/25245/
http://psasir.upm.edu.my/id/eprint/25245/1/Optimised%20crossover%20genetic%20algorithm%20for%20capacitated%20vehicle%20routing%20problem.pdf