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Adaptive memory programming for the many-to-many vehicle routing problem with cross-docking

Author

Listed:
  • Amalia I. Nikolopoulou

    (Athens University of Economics and Business)

  • Panagiotis P. Repoussis

    (Athens University of Economics and Business
    Stevens Institute of Technology)

  • Christos D. Tarantilis

    (Athens University of Economics and Business)

  • Emmanouil E. Zachariadis

    (Athens University of Economics and Business)

Abstract

This paper presents a new generalized vehicle routing problem with a cross-dock. Basic features of the examined problem are the many-to-many relationship between the suppliers and customers, and the use of different vehicle fleets for performing the inbound and outbound routes. An adaptive memory programming method has been developed coupled with a Tabu Search algorithm. For generating new provisional solutions, elite subroutes with varying lengths are identified from the reference solutions and are used as building blocks, while multiple strategies are applied to maintain an effective interplay between diversification and intensification. Various computational experiments are conducted on existing as well as on new data sets with diverse features, regarding the geographic distribution of the nodes and the density of supplier-customer links. Overall, the proposed method performed very well and new best solutions have been found. Lastly, new insights regarding the impact of split options are reported.

Suggested Citation

  • Amalia I. Nikolopoulou & Panagiotis P. Repoussis & Christos D. Tarantilis & Emmanouil E. Zachariadis, 2019. "Adaptive memory programming for the many-to-many vehicle routing problem with cross-docking," Operational Research, Springer, vol. 19(1), pages 1-38, March.
    • Handle: RePEc:spr:operea:v:19:y:2019:i:1:d:10.1007_s12351-016-0278-1
    DOI: 10.1007/s12351-016-0278-1
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    References listed on IDEAS

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    1. Zachariadis, Emmanouil E. & Tarantilis, Christos D. & Kiranoudis, Chris T., 2015. "The load-dependent vehicle routing problem and its pick-up and delivery extension," Transportation Research Part B: Methodological, Elsevier, vol. 71(C), pages 158-181.
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    11. Repoussis, Panagiotis P. & Tarantilis, Christos D. & Zachariadis, Emmanouil E., 2017. "Moving products between location pairs: Cross-docking versus direct-shippingAuthor-Name: Nikolopoulou, Amalia I," European Journal of Operational Research, Elsevier, vol. 256(3), pages 803-819.
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    Cited by:

    1. Yu Wu & Bo Zeng & Siming Huang, 2019. "A Dynamic Strategy for Home Pick-Up Service with Uncertain Customer Requests and Its Implementation," Sustainability, MDPI, vol. 11(7), pages 1-21, April.
    2. Thyago Celso C. Nepomuceno & Ana Paula Cabral Seixas Costa, 2019. "Spatial visualization on patterns of disaggregate robberies," Operational Research, Springer, vol. 19(4), pages 857-886, December.
    3. Ji, Bin & Zhang, Zheng & Yu, Samson S. & Zhou, Saiqi & Wu, Guohua, 2023. "Modelling and heuristically solving many-to-many heterogeneous vehicle routing problem with cross-docking and two-dimensional loading constraints," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1219-1235.

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