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On Modeling Stochastic Travel and Service Times in Vehicle Routing

Author

Listed:
  • Andrés Gómez

    (Centro para la Optimización y Probabilidad Aplicada (COPA), Departamento de Ingeniería Industrial, Universidad de los Andes, Bogotá, Colombia)

  • Ricardo Mariño

    (Centro para la Optimización y Probabilidad Aplicada (COPA), Departamento de Ingeniería Industrial, Universidad de los Andes, Bogotá, Colombia)

  • Raha Akhavan-Tabatabaei

    (Centro para la Optimización y Probabilidad Aplicada (COPA), Departamento de Ingeniería Industrial, Universidad de los Andes, Bogotá, Colombia)

  • Andrés L. Medaglia

    (Centro para la Optimización y Probabilidad Aplicada (COPA), Departamento de Ingeniería Industrial, Universidad de los Andes, Bogotá, Colombia)

  • Jorge E. Mendoza

    (Université Catholique de l’Ouest, LARIS (EA7315), 49008 Angers, France; and Université François-Rabelais de Tours, CNRS, LI (EA6300), OC (ERL CNRS 6305), 37200 Tours, France)

Abstract

Vehicle routing problems with stochastic travel and service times (VRPSTT) consist of designing transportation routes of minimal expected cost over a network where travel and service times are represented by random variables. Most of the existing approaches for VRPSTT are conceived to exploit the properties of the distributions assumed for the random variables. Therefore, these methods are tied to a given family of distributions and subject to strong modeling assumptions. We propose an alternative way to model travel and service times in VRPSTT without making many assumptions regarding such distributions. To illustrate our approach, we embed it into a state-of-the-art routing engine and use it to conduct experiments on instances with different travel and service time distributions.

Suggested Citation

  • Andrés Gómez & Ricardo Mariño & Raha Akhavan-Tabatabaei & Andrés L. Medaglia & Jorge E. Mendoza, 2016. "On Modeling Stochastic Travel and Service Times in Vehicle Routing," Transportation Science, INFORMS, vol. 50(2), pages 627-641, May.
    • Handle: RePEc:inm:ortrsc:v:50:y:2016:i:2:p:627-641
    DOI: 10.1287/trsc.2015.0601
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    References listed on IDEAS

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    Cited by:

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    3. David Corredor-Montenegro & Nicolás Cabrera & Raha Akhavan-Tabatabaei & Andrés L. Medaglia, 2021. "On the shortest $$\alpha$$ α -reliable path problem," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(1), pages 287-318, April.
    4. Elgesem, Aurora Smith & Skogen, Eline Sophie & Wang, Xin & Fagerholt, Kjetil, 2018. "A traveling salesman problem with pickups and deliveries and stochastic travel times: An application from chemical shipping," European Journal of Operational Research, Elsevier, vol. 269(3), pages 844-859.
    5. Chandra Ade Irawan & Majid Eskandarpour & Djamila Ouelhadj & Dylan Jones, 2019. "Simulation-based optimisation for stochastic maintenance routing in an offshore wind farm," Post-Print hal-02509382, HAL.
    6. Jorge Oyola & Halvard Arntzen & David L. Woodruff, 2018. "The stochastic vehicle routing problem, a literature review, part I: models," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 7(3), pages 193-221, September.
    7. Zhang, Jian & Woensel, Tom Van, 2023. "Dynamic vehicle routing with random requests: A literature review," International Journal of Production Economics, Elsevier, vol. 256(C).
    8. Bock, Stefan, 2020. "Optimally solving a versatile Traveling Salesman Problem on tree networks with soft due dates and multiple congestion scenarios," European Journal of Operational Research, Elsevier, vol. 283(3), pages 863-882.
    9. Irawan, Chandra Ade & Eskandarpour, Majid & Ouelhadj, Djamila & Jones, Dylan, 2021. "Simulation-based optimisation for stochastic maintenance routing in an offshore wind farm," European Journal of Operational Research, Elsevier, vol. 289(3), pages 912-926.
    10. Rafael Dawid & David McMillan & Matthew Revie, 2018. "Decision Support Tool for Offshore Wind Farm Vessel Routing under Uncertainty," Energies, MDPI, vol. 11(9), pages 1-17, August.
    11. Groß, Patrick-Oliver & Ehmke, Jan Fabian & Mattfeld, Dirk Christian, 2020. "Interval travel times for robust synchronization in city logistics vehicle routing," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 143(C).
    12. Anastasios D. Vareias & Panagiotis P. Repoussis & Panagiotis P. Repoussi, 2019. "Assessing Customer Service Reliability in Route Planning with Self-Imposed Time Windows and Stochastic Travel Times," Service Science, INFORMS, vol. 53(1), pages 256-281, February.
    13. Jorge Oyola & Halvard Arntzen & David L. Woodruff, 2017. "The stochastic vehicle routing problem, a literature review, Part II: solution methods," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 6(4), pages 349-388, December.
    14. Alexandra Anderluh & Rune Larsen & Vera C. Hemmelmayr & Pamela C. Nolz, 2020. "Impact of travel time uncertainties on the solution cost of a two-echelon vehicle routing problem with synchronization," Flexible Services and Manufacturing Journal, Springer, vol. 32(4), pages 806-828, December.

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