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Efficient Golden-Ball Algorithm Based Clustering to solve the Multi-Depot VRP With Time Windows

Author

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  • Lahcene Guezouli

    (University of Batna 2, Batna, Algeria)

  • Mohamed Bensakhria

    (University of Batna 2, Batna, Algeria)

  • Samir Abdelhamid

    (University of Batna 2, Batna, Algeria)

Abstract

In this article, the authors propose a decision support system which aims to optimize the classical Capacitated Vehicle Routing Problem by considering the existence of multiple available depots and a time window which must not be violated, that they call the Multi-Depot Vehicle Routing Problem with Time Window (MDVRPTW), and with respecting a set of criteria including: schedules requests from clients, the capacity of vehicles. The authors solve this problem by proposing a recently published technique based on soccer concepts, called Golden Ball (GB), with different solution representation from the original one, this technique was designed to solve combinatorial optimization problems, and by embedding a clustering algorithm. Computational results have shown that the approach produces acceptable quality solutions compared to the best previous results in similar problem in terms of generated solutions and processing time. Experimental results prove that the proposed Golden Ball algorithm is efficient and effective to solve the MDVRPTW problem.

Suggested Citation

  • Lahcene Guezouli & Mohamed Bensakhria & Samir Abdelhamid, 2018. "Efficient Golden-Ball Algorithm Based Clustering to solve the Multi-Depot VRP With Time Windows," International Journal of Applied Evolutionary Computation (IJAEC), IGI Global, vol. 9(1), pages 1-16, January.
    • Handle: RePEc:igg:jaec00:v:9:y:2018:i:1:p:1-16
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