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A mathematical model for vehicle routing problem under endogenous uncertainty

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  • F. Hooshmand Khaligh
  • S.A. MirHassani

Abstract

In this study, a multistage stochastic programming (SP) model is presented for a variant of single-vehicle routing problem with stochastic demands from a dynamic viewpoint. It is assumed that the actual demand of a customer becomes known only when the customer is visited. This problem falls into the category of SP with endogenous uncertainty and hence, the scenario tree is decision-dependent. Therefore, nonanticipativity of decisions is ensured by conditional constraints making up a large portion of total constraints. Thus, a novel approach is proposed that considerably reduces the problem size without any effect on the solution space. Computational results on some test problems are reported.

Suggested Citation

  • F. Hooshmand Khaligh & S.A. MirHassani, 2016. "A mathematical model for vehicle routing problem under endogenous uncertainty," International Journal of Production Research, Taylor & Francis Journals, vol. 54(2), pages 579-590, January.
    • Handle: RePEc:taf:tprsxx:v:54:y:2016:i:2:p:579-590
    DOI: 10.1080/00207543.2015.1057625
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    References listed on IDEAS

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    Cited by:

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    2. Nilay Noyan & Gábor Rudolf & Miguel Lejeune, 2022. "Distributionally Robust Optimization Under a Decision-Dependent Ambiguity Set with Applications to Machine Scheduling and Humanitarian Logistics," INFORMS Journal on Computing, INFORMS, vol. 34(2), pages 729-751, March.
    3. Jose Escribano Macias & Nils Goldbeck & Pei-Yuan Hsu & Panagiotis Angeloudis & Washington Ochieng, 2020. "Endogenous stochastic optimisation for relief distribution assisted with unmanned aerial vehicles," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 42(4), pages 1089-1125, December.
    4. Abdoli, B. & Hooshmand, F. & MirHassani, S.A., 2023. "A novel stochastic programming model under endogenous uncertainty for the CCS-EOR planning problem," Applied Energy, Elsevier, vol. 338(C).
    5. Feng, Wei & Feng, Yiping & Zhang, Qi, 2021. "Multistage robust mixed-integer optimization under endogenous uncertainty," European Journal of Operational Research, Elsevier, vol. 294(2), pages 460-475.
    6. F. Hooshmand & S. A. MirHassani, 2018. "Reduction of nonanticipativity constraints in multistage stochastic programming problems with endogenous and exogenous uncertainty," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 87(1), pages 1-18, February.

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