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A Branch-Cut-and-Price Algorithm for the Energy Minimization Vehicle Routing Problem

Author

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  • Ricardo Fukasawa

    (Department of Combinatorics and Optimization, Faculty of Mathematics, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada)

  • Qie He

    (Department of Industrial and Systems Engineering, University of Minnesota, Minneapolis, Minnesota 55455)

  • Yongjia Song

    (Department of Statistical Sciences and Operations Research, Virginia Commonwealth University, Richmond, Virginia 23284)

Abstract

We study a variant of the capacitated vehicle routing problem where the cost over each arc is defined as the product of the arc length and the weight of the vehicle when it traverses that arc. We propose two new mixed-integer linear programming formulations for the problem: an arc-load formulation and a set partitioning formulation based on q -routes with additional constraints. A family of cycle elimination constraints are derived for the arc-load formulation. We then compare the linear programming (LP) relaxations of these formulations with the two-index one-commodity flow formulation proposed in the literature. In particular, we show that the arc-load formulation with the new cycle elimination constraints gives the same LP bound as the set partitioning formulation based on 2-cycle-free q -routes, which is stronger than the LP bound given by the two-index one-commodity flow formulation. We propose a branch-and-cut algorithm for the arc-load formulation, and a branch-cut-and-price algorithm for the set partitioning formulation strengthened by additional constraints. Computational results on instances from the literature demonstrate that a significant improvement can be achieved by the branch-cut-and-price algorithm over other methods.

Suggested Citation

  • Ricardo Fukasawa & Qie He & Yongjia Song, 2016. "A Branch-Cut-and-Price Algorithm for the Energy Minimization Vehicle Routing Problem," Transportation Science, INFORMS, vol. 50(1), pages 23-34, February.
  • Handle: RePEc:inm:ortrsc:v:50:y:2016:i:1:p:23-34
    DOI: 10.1287/trsc.2015.0593
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    References listed on IDEAS

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    Cited by:

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    2. Huang, Sen & Liu, Kanglin & Zhang, Zhi-Hai, 2023. "Column-and-constraint-generation-based approach to a robust reverse logistic network design for bike sharing," Transportation Research Part B: Methodological, Elsevier, vol. 173(C), pages 90-118.
    3. Sun, Wei & Yu, Yang & Wang, Junwei, 2019. "Heterogeneous vehicle pickup and delivery problems: Formulation and exact solution," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 181-202.
    4. Liu, Yiming & Roberto, Baldacci & Zhou, Jianwen & Yu, Yang & Zhang, Yu & Sun, Wei, 2023. "Efficient feasibility checks and an adaptive large neighborhood search algorithm for the time-dependent green vehicle routing problem with time windows," European Journal of Operational Research, Elsevier, vol. 310(1), pages 133-155.
    5. Sina Rastani & Bülent Çatay, 2023. "A large neighborhood search-based matheuristic for the load-dependent electric vehicle routing problem with time windows," Annals of Operations Research, Springer, vol. 324(1), pages 761-793, May.
    6. Fukasawa, Ricardo & He, Qie & Song, Yongjia, 2016. "A disjunctive convex programming approach to the pollution-routing problem," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 61-79.
    7. Canan G. Corlu & Rocio de la Torre & Adrian Serrano-Hernandez & Angel A. Juan & Javier Faulin, 2020. "Optimizing Energy Consumption in Transportation: Literature Review, Insights, and Research Opportunities," Energies, MDPI, vol. 13(5), pages 1-33, March.
    8. Luciano Costa & Claudio Contardo & Guy Desaulniers, 2019. "Exact Branch-Price-and-Cut Algorithms for Vehicle Routing," Transportation Science, INFORMS, vol. 53(4), pages 946-985, July.
    9. Thomas Kirschstein & Arne Heinold & Martin Behnke & Frank Meisel & Christian Bierwirth, 2022. "Eco‐labeling of freight transport services: Design, evaluation, and research directions," Journal of Industrial Ecology, Yale University, vol. 26(3), pages 801-814, June.

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