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Handling uncertainties in vehicle routing problems through data preprocessing

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  • Chardy, Matthieu
  • Klopfenstein, Olivier

Abstract

This paper presents a global preprocessing methodology for handling uncertainties in operations management. Beyond theoretical considerations on solution feasibility, the methodology provides practitioners with a Monte Carlo simulation-based framework for effective risk management. The main strength of this methodology is being easily applicable to almost any decision problem. Application field of the paper is a real-life workforce management problem for which we propose several mixed integer formulations as well as dedicated solution algorithms. Extensive numerical tests on real-life instances assess the benefit from preprocessing schemes when performed as recommended by our approach, and thus prove its practical relevance.

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  • Chardy, Matthieu & Klopfenstein, Olivier, 2012. "Handling uncertainties in vehicle routing problems through data preprocessing," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(3), pages 667-683.
    • Handle: RePEc:eee:transe:v:48:y:2012:i:3:p:667-683
    DOI: 10.1016/j.tre.2011.12.001
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    References listed on IDEAS

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    Cited by:

    1. Evers, Lanah & Barros, Ana Isabel & Monsuur, Herman & Wagelmans, Albert, 2014. "Online stochastic UAV mission planning with time windows and time-sensitive targets," European Journal of Operational Research, Elsevier, vol. 238(1), pages 348-362.
    2. Maria João Santos & Pedro Amorim & Alexandra Marques & Ana Carvalho & Ana Póvoa, 2020. "The vehicle routing problem with backhauls towards a sustainability perspective: a review," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(2), pages 358-401, July.
    3. Enrico Bartolini & Dominik Goeke & Michael Schneider & Mengdie Ye, 2021. "The Robust Traveling Salesman Problem with Time Windows Under Knapsack-Constrained Travel Time Uncertainty," Transportation Science, INFORMS, vol. 55(2), pages 371-394, March.
    4. Santos, Maria João & Curcio, Eduardo & Mulati, Mauro Henrique & Amorim, Pedro & Miyazawa, Flávio Keidi, 2020. "A robust optimization approach for the vehicle routing problem with selective backhauls," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).

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