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A cluster first-route second approach for a capacitated vehicle routing problem: a case study

Author

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  • Serap Ercan Comert
  • Harun Resit Yazgan
  • Sena Kır
  • Furkan Yener

Abstract

In this study, a capacitated vehicle routing problem (CVRP) which dealt with minimum distance routes for vehicles that serve customers having specific demands from a common warehouse under a capacity constraint. This problem is NP hard. We solved the problem in a hierarchical way (i.e., cluster-first route-second method). Firstly, customers were clustered using three different clustering algorithms; K-means, K-medoids and random clustering with considering a vehicle capacity. Secondly, routing problems for each cluster were solved using a branch and bound algorithm. The proposed solution strategy was employed on a case study in a supermarket chain. Results of numerical investigation were presented to illustrate the effectiveness of the algorithms using paired sample t tests. The results illustrated that the K-medoids algorithm provided better solution than the others.

Suggested Citation

  • Serap Ercan Comert & Harun Resit Yazgan & Sena Kır & Furkan Yener, 2018. "A cluster first-route second approach for a capacitated vehicle routing problem: a case study," International Journal of Procurement Management, Inderscience Enterprises Ltd, vol. 11(4), pages 399-419.
    • Handle: RePEc:ids:ijpman:v:11:y:2018:i:4:p:399-419
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    Cited by:

    1. Ouyang, Zhiyuan & Leung, Eric K.H. & Huang, George Q., 2023. "Community logistics and dynamic community partitioning: A new approach for solving e-commerce last mile delivery," European Journal of Operational Research, Elsevier, vol. 307(1), pages 140-156.
    2. Sean Grogan & Robert Pellerin & Michel Gamache, 2021. "Using tornado-related weather data to route unmanned aerial vehicles to locate damage and victims," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(4), pages 905-939, December.

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