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Clustering algorithms for consolidation of customer orders into vehicle shipments

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  • Koskosidis, Yiannis A.
  • Powell, Warren B.

Abstract

The consolidation of shipments into loads arises in a number of applications, including household moving, truckload trucking, rail and container operations. The capacitated clustering problem (CCP) is one of the underlying optimization problems for the efficient consolidation of customer orders to vehicle shipments. In this paper we develop optimization-based heuristic algorithms for the CCP, extending procedures developed by Mulvey and Beck, as well as algorithms developed by Fisher and Jaikumar, for the generalized assignment problem. In this paper, iterative methods are proposed that avoid the specification of "seed" customers required by other algorithms, and which are shown to produce better solutions than existing heuristics. Lagrangian relaxations are used to develop rigorous bounds, which demonstrate the effectiveness of relatively simple heuristics.

Suggested Citation

  • Koskosidis, Yiannis A. & Powell, Warren B., 1992. "Clustering algorithms for consolidation of customer orders into vehicle shipments," Transportation Research Part B: Methodological, Elsevier, vol. 26(5), pages 365-379, October.
    • Handle: RePEc:eee:transb:v:26:y:1992:i:5:p:365-379
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    Cited by:

    1. Song, Ruidian & Zhao, Lei & Van Woensel, Tom & Fransoo, Jan C., 2019. "Coordinated delivery in urban retail," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 126(C), pages 122-148.
    2. Belarmino Adenso-Díaz & Mónica González & Emérita García, 1998. "A Hierarchical Approach to Managing Dairy Routing," Interfaces, INFORMS, vol. 28(2), pages 21-31, April.
    3. Scheuerer, Stephan & Wendolsky, Rolf, 2006. "A scatter search heuristic for the capacitated clustering problem," European Journal of Operational Research, Elsevier, vol. 169(2), pages 533-547, March.
    4. Lu Han & Dachuan Xu & Donglei Du & Dongmei Zhang, 0. "An approximation algorithm for the uniform capacitated k-means problem," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-12.
    5. Fleszar, K. & Hindi, K.S., 2008. "An effective VNS for the capacitated p-median problem," European Journal of Operational Research, Elsevier, vol. 191(3), pages 612-622, December.
    6. Ahmadi, Samad & Osman, Ibrahim H., 2005. "Greedy random adaptive memory programming search for the capacitated clustering problem," European Journal of Operational Research, Elsevier, vol. 162(1), pages 30-44, April.
    7. Wooseung Jang & Huay H. Lim & Thomas J. Crowe & Gail Raskin & Thomas E. Perkins, 2006. "The Missouri Lottery Optimizes Its Scheduling and Routing to Improve Efficiency and Balance," Interfaces, INFORMS, vol. 36(4), pages 302-313, August.
    8. Lu Han & Dachuan Xu & Donglei Du & Dongmei Zhang, 2022. "An approximation algorithm for the uniform capacitated k-means problem," Journal of Combinatorial Optimization, Springer, vol. 44(3), pages 1812-1823, October.
    9. A I Jarrah & J F Bard, 2011. "Pickup and delivery network segmentation using contiguous geographic clustering," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(10), pages 1827-1843, October.
    10. Lau, Kwok Hung, 2013. "Measuring distribution efficiency of a retail network through data envelopment analysis," International Journal of Production Economics, Elsevier, vol. 146(2), pages 598-611.
    11. Kijmanawat, Kerati & Ieda, Hitoshi, 2005. "Development and Application of CM-GATS Algorithms in Solving Large Multilevel Hierarchical Network Design Problems," Research in Transportation Economics, Elsevier, vol. 13(1), pages 121-142, January.
    12. I H Osman & S Ahmadi, 2007. "Guided construction search metaheuristics for the capacitated p-median problem with single source constraint," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(1), pages 100-114, January.
    13. Zhou, Qing & Benlic, Una & Wu, Qinghua & Hao, Jin-Kao, 2019. "Heuristic search to the capacitated clustering problem," European Journal of Operational Research, Elsevier, vol. 273(2), pages 464-487.
    14. Bard, Jonathan F. & Jarrah, Ahmad I., 2009. "Large-scale constrained clustering for rationalizing pickup and delivery operations," Transportation Research Part B: Methodological, Elsevier, vol. 43(5), pages 542-561, June.

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