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A new enhancement of the Clarke and Wright savings heuristic for the capacitated vehicle routing problem

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  • İ K Altınel

    (Boǧaziçi University, Bebek)

  • T Öncan

    (Galatasaray University, Ortaköy)

Abstract

In this work we are concerned with the Clarke–Wright savings method for the classical capacitated vehicle routing problem. This is an NP-hard problem and numerous heuristic solution methods have been proposed. They can be classified as the classical ones and metaheuristics. Recent developments have shown that classical heuristics do not compare with the best metaheuristic implementations. However, some of them are very fast and simple to implement. This explains the popularity of the Clarke–Wright savings method in practice and the motivation behind its enhancements. We follow this line of research and propose a new enhancement which differs from the previous ones in its saving criterion: Customer demands are considered in addition to distances. Based on the extensive computational experiments we can say that the new method is not only very fast but also very accurate.

Suggested Citation

  • İ K Altınel & T Öncan, 2005. "A new enhancement of the Clarke and Wright savings heuristic for the capacitated vehicle routing problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(8), pages 954-961, August.
    • Handle: RePEc:pal:jorsoc:v:56:y:2005:i:8:d:10.1057_palgrave.jors.2601916
    DOI: 10.1057/palgrave.jors.2601916
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    References listed on IDEAS

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    1. S Salhi & G Nagy, 1999. "A cluster insertion heuristic for single and multiple depot vehicle routing problems with backhauling," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 50(10), pages 1034-1042, October.
    2. Paessens, H., 1988. "The savings algorithm for the vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 34(3), pages 336-344, March.
    3. Vigo, Daniele, 1996. "A heuristic algorithm for the asymmetric capacitated vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 89(1), pages 108-126, February.
    4. Wade, A. C. & Salhi, S., 2002. "An investigation into a new class of vehicle routing problem with backhauls," Omega, Elsevier, vol. 30(6), pages 479-487, December.
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    Cited by:

    1. M. Kritikos & G. Ioannou, 2017. "A greedy heuristic for the capacitated minimum spanning tree problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(10), pages 1223-1235, October.
    2. Chang, Ximing & Wu, Jianjun & Sun, Huijun & Correia, Gonçalo Homem de Almeida & Chen, Jianhua, 2021. "Relocating operational and damaged bikes in free-floating systems: A data-driven modeling framework for level of service enhancement," Transportation Research Part A: Policy and Practice, Elsevier, vol. 153(C), pages 235-260.
    3. Merve Cengiz Toklu, 2023. "A fuzzy multi-criteria approach based on Clarke and Wright savings algorithm for vehicle routing problem in humanitarian aid distribution," Journal of Intelligent Manufacturing, Springer, vol. 34(5), pages 2241-2261, June.
    4. Yuan Zhang & Yu Yuan & Kejing Lu, 2020. "RETRACTED ARTICLE: E-commerce information system data analytics by advanced ACO for asymmetric capacitated vehicle delivery routing," Information Systems and e-Business Management, Springer, vol. 18(4), pages 911-929, December.
    5. Emre Tokgöz & Samir Alwazzi & Theodore Trafalis, 2015. "A heuristic algorithm to solve the single-facility location routing problem on Riemannian surfaces," Computational Management Science, Springer, vol. 12(3), pages 397-415, July.

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    heuristics; vehicle routing problem;

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