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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Bibliographic Details
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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Summary: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.