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A Joint Vehicle Routing and Speed Optimization Problem

Author

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  • Ricardo Fukasawa

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

  • Qie He

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

  • Fernando Santos

    (Department of Engineering, Campus Itabira, Federal University of Itajubá, Itajubá, Brazil)

  • Yongjia Song

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

Abstract

Classic vehicle routing models usually treat fuel cost as input data, but fuel consumption heavily depends on the travel speed, which leads to the study of optimizing speeds over a route to improve fuel efficiency. In this paper, we propose a joint vehicle routing and speed optimization problem to minimize the total operating cost including fuel cost. The only assumption made on the dependence between fuel cost and travel speed is that it is a strictly convex differentiable function. This problem is very challenging, with medium-sized instances already difficult for a general mixed-integer convex optimization solver. We propose a novel set-partitioning formulation and a branch-cut-and-price algorithm to solve this problem. We introduce new dominance rules for the labeling algorithm so that the pricing problem can be solved efficiently. Our algorithm clearly outperforms the off-the-shelf optimization solver, and is able to solve some benchmark instances to optimality for the first time. The online supplement is available at https://doi.org/10.1287/ijoc.2018.0810 .

Suggested Citation

  • Ricardo Fukasawa & Qie He & Fernando Santos & Yongjia Song, 2018. "A Joint Vehicle Routing and Speed Optimization Problem," INFORMS Journal on Computing, INFORMS, vol. 30(4), pages 694-709, November.
    • Handle: RePEc:inm:orijoc:v:30:y:2018:i:4:p:694-709
    DOI: 10.1287/ijoc.2018.0810
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    References listed on IDEAS

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    Cited by:

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    3. Zeyang Wu & Kameng Nip & Qie He, 2021. "A New Combinatorial Algorithm for Separable Convex Resource Allocation with Nested Bound Constraints," INFORMS Journal on Computing, INFORMS, vol. 33(3), pages 1197-1212, July.

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