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Moving products between location pairs: Cross-docking versus direct-shippingAuthor-Name: Nikolopoulou, Amalia I

Author

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  • Repoussis, Panagiotis P.
  • Tarantilis, Christos D.
  • Zachariadis, Emmanouil E.

Abstract

This work considers the problem of satisfying transportation requests from a set of suppliers to a set of customers. Each request calls for moving products between a pick-up and a delivery location pair. A commonly adopted approach is the direct-shipping of products, without using intermediate transshipment points, or in-transit merge of shipments. Another alternative strategy that often appears in practice is to use an intermediate cross-dock facility, acting as a consolidation point for transported products. The goal of this paper is to evaluate these inherently different distribution options and to conduct a comprehensive comparative analysis regarding their cost-effectiveness. For this purpose, a local-search optimization framework has been developed. The optimization framework is tested on existing, as well as new benchmark data sets. Various computational experiments have been performed, to analyze the impact of several spatial and temporal characteristics, such as the geographic distribution of customers and suppliers, the proximity of individual pick-up and delivery pairs, the positioning of the depot, the tightness of the capacity and duration constraints, and the time required to handle and consolidate shipments at the cross-dock. The results of the computational experiments are further analyzed through a logistic regression analysis, in order to identify the characteristics that affect the relative effectiveness of the two compared strategies. In addition, a mixed model considering both direct-shipping and cross-docking is tackled by appropriately extending the proposed local-search framework.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ejores:v:256:y:2017:i:3:p:803-819
    DOI: 10.1016/j.ejor.2016.06.053
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    Cited by:

    1. 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.
    2. 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.
    3. Stavropoulou, F. & Repoussis, P.P. & Tarantilis, C.D., 2019. "The Vehicle Routing Problem with Profits and consistency constraints," European Journal of Operational Research, Elsevier, vol. 274(1), pages 340-356.
    4. Zhen, Lu & Hu, Yi & Wang, Shuaian & Laporte, Gilbert & Wu, Yiwei, 2019. "Fleet deployment and demand fulfillment for container shipping liners," Transportation Research Part B: Methodological, Elsevier, vol. 120(C), pages 15-32.
    5. Saeid Nasrollahi & Hasan Hosseini-Nasab & Mohammad Bagher Fakhrzad & Mahboobeh Honarvar, 2023. "A multi-stage stochastic model for designing a linked cross-docking distribution network with heterogeneous trucks," Operational Research, Springer, vol. 23(1), pages 1-41, March.

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