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Restocking-Based Rollout Policies for the Vehicle Routing Problem with Stochastic Demand and Duration Limits

Author

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  • Justin C. Goodson

    (Department of Operations and Information Technology Management, John Cook School of Business, Saint Louis University, St. Louis, Missouri 63108)

  • Barrett W. Thomas

    (Department of Management Sciences, Tippie College of Business, University of Iowa, Iowa City, Iowa 52242)

  • Jeffrey W. Ohlmann

    (Department of Management Sciences, Tippie College of Business, University of Iowa, Iowa City, Iowa 52242)

Abstract

We develop restocking-based rollout policies to make real-time, dynamic routing decisions for the vehicle routing problem with stochastic demand and duration limits . Leveraging dominance results, we develop a computationally tractable method to estimate the value of an optimal restocking policy along a fixed route. Embedding our procedure in rollout algorithms, we show restocking-based rollout outperforms a priori-based rollout, demonstrating the value of explicitly considering preemptive capacity replenishment in a rollout approach for dynamic routing. We also demonstrate the effectiveness of basic local search versus more sophisticated mechanisms for the heuristic component of the rollout procedure.

Suggested Citation

  • Justin C. Goodson & Barrett W. Thomas & Jeffrey W. Ohlmann, 2016. "Restocking-Based Rollout Policies for the Vehicle Routing Problem with Stochastic Demand and Duration Limits," Transportation Science, INFORMS, vol. 50(2), pages 591-607, May.
    • Handle: RePEc:inm:ortrsc:v:50:y:2016:i:2:p:591-607
    DOI: 10.1287/trsc.2015.0591
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    References listed on IDEAS

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    Cited by:

    1. Wadi Khalid Anuar & Lai Soon Lee & Hsin-Vonn Seow & Stefan Pickl, 2021. "A Multi-Depot Vehicle Routing Problem with Stochastic Road Capacity and Reduced Two-Stage Stochastic Integer Linear Programming Models for Rollout Algorithm," Mathematics, MDPI, vol. 9(13), pages 1-44, July.
    2. Majid Salavati-Khoshghalb & Michel Gendreau & Ola Jabali & Walter Rei, 2019. "A Rule-Based Recourse for the Vehicle Routing Problem with Stochastic Demands," Transportation Science, INFORMS, vol. 53(5), pages 1334-1353, September.
    3. Marlin W. Ulmer & Barrett W. Thomas & Dirk C. Mattfeld, 2019. "Preemptive depot returns for dynamic same-day delivery," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 8(4), pages 327-361, December.
    4. Klapp, Mathias A. & Erera, Alan L. & Toriello, Alejandro, 2018. "The Dynamic Dispatch Waves Problem for same-day delivery," European Journal of Operational Research, Elsevier, vol. 271(2), pages 519-534.
    5. Marlin W. Ulmer & Barrett W. Thomas, 2019. "Enough Waiting for the Cable Guy—Estimating Arrival Times for Service Vehicle Routing," Transportation Science, INFORMS, vol. 53(3), pages 897-916, May.
    6. Soeffker, Ninja & Ulmer, Marlin W. & Mattfeld, Dirk C., 2022. "Stochastic dynamic vehicle routing in the light of prescriptive analytics: A review," European Journal of Operational Research, Elsevier, vol. 298(3), pages 801-820.
    7. Marlin W. Ulmer, 2020. "Horizontal combinations of online and offline approximate dynamic programming for stochastic dynamic vehicle routing," 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. 28(1), pages 279-308, March.
    8. Zhang, Jian & Woensel, Tom Van, 2023. "Dynamic vehicle routing with random requests: A literature review," International Journal of Production Economics, Elsevier, vol. 256(C).
    9. Shu Zhang & Jeffrey W. Ohlmann & Barrett W. Thomas, 2018. "Dynamic Orienteering on a Network of Queues," Transportation Science, INFORMS, vol. 52(3), pages 691-706, June.
    10. Bertazzi, Luca & Secomandi, Nicola, 2018. "Faster rollout search for the vehicle routing problem with stochastic demands and restocking," European Journal of Operational Research, Elsevier, vol. 270(2), pages 487-497.
    11. Daniel R. Jiang & Lina Al-Kanj & Warren B. Powell, 2020. "Optimistic Monte Carlo Tree Search with Sampled Information Relaxation Dual Bounds," Operations Research, INFORMS, vol. 68(6), pages 1678-1697, November.
    12. Yang, Meng & Ni, Yaodong & Song, Qinyu, 2022. "Optimizing driver consistency in the vehicle routing problem under uncertain environment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    13. Wadi Khalid Anuar & Lai Soon Lee & Hsin-Vonn Seow & Stefan Pickl, 2022. "A Multi-Depot Dynamic Vehicle Routing Problem with Stochastic Road Capacity: An MDP Model and Dynamic Policy for Post-Decision State Rollout Algorithm in Reinforcement Learning," Mathematics, MDPI, vol. 10(15), pages 1-70, July.
    14. Goodson, Justin C. & Thomas, Barrett W. & Ohlmann, Jeffrey W., 2017. "A rollout algorithm framework for heuristic solutions to finite-horizon stochastic dynamic programs," European Journal of Operational Research, Elsevier, vol. 258(1), pages 216-229.
    15. Florio, Alexandre M. & Hartl, Richard F. & Minner, Stefan, 2020. "Optimal a priori tour and restocking policy for the single-vehicle routing problem with stochastic demands," European Journal of Operational Research, Elsevier, vol. 285(1), pages 172-182.
    16. Ulmer, Marlin W. & Thomas, Barrett W., 2020. "Meso-parametric value function approximation for dynamic customer acceptances in delivery routing," European Journal of Operational Research, Elsevier, vol. 285(1), pages 183-195.
    17. Klapp, Mathias A. & Erera, Alan L. & Toriello, Alejandro, 2020. "Request acceptance in same-day delivery," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 143(C).
    18. Alexandre M. Florio & Richard F. Hartl & Stefan Minner & Juan-José Salazar-González, 2021. "A Branch-and-Price Algorithm for the Vehicle Routing Problem with Stochastic Demands and Probabilistic Duration Constraints," Transportation Science, INFORMS, vol. 55(1), pages 122-138, 1-2.
    19. Marlin W. Ulmer & Justin C. Goodson & Dirk C. Mattfeld & Marco Hennig, 2019. "Offline–Online Approximate Dynamic Programming for Dynamic Vehicle Routing with Stochastic Requests," Service Science, INFORMS, vol. 53(1), pages 185-202, February.

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