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A recovery model for combinational disruptions in logistics delivery: Considering the real-world participators

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  • Wang, Xuping
  • Ruan, Junhu
  • Shi, Yan

Abstract

The existence of uncertainties may result in various unexpected disruption events in logistics delivery, which often makes actual delivery operations deviate from intended plans. The purpose of the paper is to develop a combinational disruption recovery model for vehicle routing problem with time windows (VRPTW), trying to handle a variety and a combination of delivery disruption events. Firstly, a novel approach to measure new-adding customer disruption, which considers the real-world participators (mainly including customers, drivers and logistics providers) in VRPTW, is developed. Then the paper proposes methods of transforming various delivery disruptions into the new-adding customer disruption, and determines the optimal starting times of delivery vehicles from the depot to provide a new rescue strategy (called starting later policy) for disrupted VRPTW. Based on the above, a combinational disruption recovery model for VRPTW is constructed and nested partition method (NPM) is designed to solve the proposed model. Finally, computational results are reported and compared with those of previous works, which verifies the effectiveness of the proposed solution and draws some interesting conclusions.

Suggested Citation

  • Wang, Xuping & Ruan, Junhu & Shi, Yan, 2012. "A recovery model for combinational disruptions in logistics delivery: Considering the real-world participators," International Journal of Production Economics, Elsevier, vol. 140(1), pages 508-520.
    • Handle: RePEc:eee:proeco:v:140:y:2012:i:1:p:508-520
    DOI: 10.1016/j.ijpe.2012.07.001
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    3. Wang, Jianxin & Lim, Ming K. & Zhan, Yuanzhu & Wang, XiaoFeng, 2020. "An intelligent logistics service system for enhancing dispatching operations in an IoT environment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 135(C).
    4. Giménez-Palacios, Iván & Parreño, Francisco & Álvarez-Valdés, Ramón & Paquay, Célia & Oliveira, Beatriz Brito & Carravilla, Maria Antónia & Oliveira, José Fernando, 2022. "First-mile logistics parcel pickup: Vehicle routing with packing constraints under disruption," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    5. Richard Eglese & Sofoclis Zambirinis, 2018. "Disruption management in vehicle routing and scheduling for road freight transport: a review," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(1), pages 1-17, April.
    6. Anne Meyer & Suad Sejdovic & Katharina Glock & Matthias Bender & Natalja Kleiner & Dominik Riemer, 2018. "A disruption management system for automotive inbound networks: concepts and challenges," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 7(1), pages 25-56, March.
    7. Jafarian, Ahmad & Asgari, Nasrin & Mohri, Seyed Sina & Fatemi-Sadr, Elham & Farahani, Reza Zanjirani, 2019. "The inventory-routing problem subject to vehicle failure," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 126(C), pages 254-294.
    8. Junhu Ruan & Xuping Wang & Yan Shi, 2014. "A Two-Stage Approach for Medical Supplies Intermodal Transportation in Large-Scale Disaster Responses," IJERPH, MDPI, vol. 11(11), pages 1-29, October.
    9. Ahmadi-Javid, Amir & Seddighi, Amir Hossein, 2013. "A location-routing problem with disruption risk," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 53(C), pages 63-82.

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