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Vehicle routing problem in omni-channel retailing distribution systems

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  • Abdulkader, M.M.S.
  • Gajpal, Yuvraj
  • ElMekkawy, Tarek Y.

Abstract

This paper introduces a variant of the vehicle routing problem where a group of retail stores are served from a distribution center using a fleet of vehicles. Moreover, products are distributed to consumers from some of these retail stores based on product availability at inventory and by means of the same fleet of vehicles. This variant of the vehicle routing problem can be found in omni-channel retail distribution systems. Retail distribution systems are considered omni- or multi-channel systems when consumers can either place orders online or physically visit the stores to buy the products. In this problem, the decisions of assigning consumers to retail stores based on inventory availability are combined with finding the routes of vehicles. The new problem can be considered a generalization of both capacitated vehicle routing problem and the pickup and delivery problem. The paper presents a mathematical formulation to describe this problem and proposes two solution approaches (two-phase heuristic and multi-ant colony algorithm). We also generate new benchmark problem instances to evaluate the performance of the proposed solution approaches.

Suggested Citation

  • Abdulkader, M.M.S. & Gajpal, Yuvraj & ElMekkawy, Tarek Y., 2018. "Vehicle routing problem in omni-channel retailing distribution systems," International Journal of Production Economics, Elsevier, vol. 196(C), pages 43-55.
    • Handle: RePEc:eee:proeco:v:196:y:2018:i:c:p:43-55
    DOI: 10.1016/j.ijpe.2017.11.011
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    Cited by:

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    2. Hübner, Alexander & Hense, Jonas & Dethlefs, Christian, 2022. "The revival of retail stores via omnichannel operations: A literature review and research framework," European Journal of Operational Research, Elsevier, vol. 302(3), pages 799-818.
    3. Loske, Dominic & Klumpp, Matthias, 2021. "Human-AI collaboration in route planning: An empirical efficiency-based analysis in retail logistics," International Journal of Production Economics, Elsevier, vol. 241(C).
    4. Cai, Ya-Jun & Lo, Chris K.Y., 2020. "Omni-channel management in the new retailing era: A systematic review and future research agenda," International Journal of Production Economics, Elsevier, vol. 229(C).
    5. Ozgur Kabadurmus & Mehmet S. Erdogan, 2023. "A green vehicle routing problem with multi-depot, multi-tour, heterogeneous fleet and split deliveries: a mathematical model and heuristic approach," Journal of Combinatorial Optimization, Springer, vol. 45(3), pages 1-29, April.
    6. Zhang, Jie & Meng, Meng & Wong, Yiik Diew & Ieromonachou, Petros & Wang, David Z.W., 2021. "A data-driven dynamic repositioning model in bicycle-sharing systems," International Journal of Production Economics, Elsevier, vol. 231(C).
    7. Gupta, Vishal Kumar & Ting, Q.U. & Tiwari, Manoj Kumar, 2019. "Multi-period price optimization problem for omnichannel retailers accounting for customer heterogeneity," International Journal of Production Economics, Elsevier, vol. 212(C), pages 155-167.
    8. Surendra Reddy Kancharla & Gitakrishnan Ramadurai, 2019. "Multi-depot Two-Echelon Fuel Minimizing Routing Problem with Heterogeneous Fleets: Model and Heuristic," Networks and Spatial Economics, Springer, vol. 19(3), pages 969-1005, September.
    9. Xueqi Wu & Zhi‐Long Chen, 2022. "Fulfillment scheduling for buy‐online‐pickup‐in‐store orders," Production and Operations Management, Production and Operations Management Society, vol. 31(7), pages 2982-3003, July.

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