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Robust optimization for the vehicle routing problem with multiple deliverymen

Author

Listed:
  • Jonathan De La Vega

    (Federal University of São Carlos)

  • Pedro Munari

    (Federal University of São Carlos)

  • Reinaldo Morabito

    (Federal University of São Carlos)

Abstract

This paper addresses the vehicle routing problem with time windows and multiple deliverymen in which the customer demands are uncertain and belong to a predetermined polytope. In addition to the routing decisions, this problem attempts to define the number of deliverymen used to service to the customers on each route. A new mathematical formulation is presented for the deterministic counterpart based on auxiliary variables that define the assignment of customers to routes. Building on this formulation, we apply a static robust optimization approach to obtain a robust counterpart formulation that captures the random nature of customer demand. Due to the difficulty in solving this formulation, we propose a constructive heuristic to generate a robust solution, which is used as a starting point for solving the robust counterpart formulation. The heuristic is an extension of Solomon’s heuristic I1. Computational results using problem instances from the literature and risk analysis via Monte-Carlo simulation indicate the potential of static robust optimization to address the trade-off between cost and risk. The results also reveal that the proposed approach provides good results even without exact knowledge of some probabilistic measure of the customer demand.

Suggested Citation

  • Jonathan De La Vega & Pedro Munari & Reinaldo Morabito, 2019. "Robust optimization for the vehicle routing problem with multiple deliverymen," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 27(4), pages 905-936, December.
  • Handle: RePEc:spr:cejnor:v:27:y:2019:i:4:d:10.1007_s10100-017-0511-x
    DOI: 10.1007/s10100-017-0511-x
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    References listed on IDEAS

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    Cited by:

    1. De La Vega, Jonathan & Gendreau, Michel & Morabito, Reinaldo & Munari, Pedro & Ordóñez, Fernando, 2023. "An integer L-shaped algorithm for the vehicle routing problem with time windows and stochastic demands," European Journal of Operational Research, Elsevier, vol. 308(2), pages 676-695.
    2. Yu, Vincent F. & Anh, Pham Tuan & Baldacci, Roberto, 2023. "A robust optimization approach for the vehicle routing problem with cross-docking under demand uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 173(C).
    3. Wu, Lingxiao & Wang, Shuaian & Laporte, Gilbert, 2021. "The Robust Bulk Ship Routing Problem with Batched Cargo Selection," Transportation Research Part B: Methodological, Elsevier, vol. 143(C), pages 124-159.
    4. Aura Jalal & Aldair Alvarez & Cesar Alvarez-Cruz & Jonathan La Vega & Alfredo Moreno, 2023. "The robust multi-plant capacitated lot-sizing problem," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(2), pages 302-330, July.
    5. Jonathan De La Vega & Alfredo Moreno & Reinaldo Morabito & Pedro Munari, 2023. "A robust optimization approach for the unrelated parallel machine scheduling problem," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(1), pages 31-66, April.
    6. Xianlong Ge & Yuanzhi Jin, 2023. "Sustainability Oriented Vehicle Route Planning Based on Time-Dependent Arc Travel Durations," Sustainability, MDPI, vol. 15(4), pages 1-25, February.

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