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The demand weighted vehicle routing problem

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  • Camm, Jeffrey D.
  • Magazine, Michael J.
  • Kuppusamy, Saravanan
  • Martin, Kipp

Abstract

In this paper, we present an exact method for the demand weighted vehicle routing problem. This problem arises when the objective is to minimize the distance traveled by the vehicles weighted by the number of passengers on the routes. The resulting model is a non-convex, mixed-integer quadratic program and we show how to reformulate this problem as a linear integer program with auxiliary variables. The reformulation provides very tight lower bounds on the optimal solution value and little enumeration is required. However, the reformulated model is very large and therefore, it is solved with a branch, price and cut algorithm. Using COIN-OR software, we provide computational results with actual data from a large urban university.

Suggested Citation

  • Camm, Jeffrey D. & Magazine, Michael J. & Kuppusamy, Saravanan & Martin, Kipp, 2017. "The demand weighted vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 262(1), pages 151-162.
    • Handle: RePEc:eee:ejores:v:262:y:2017:i:1:p:151-162
    DOI: 10.1016/j.ejor.2017.03.033
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    References listed on IDEAS

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    1. Dumas, Yvan & Desrosiers, Jacques & Soumis, Francois, 1991. "The pickup and delivery problem with time windows," European Journal of Operational Research, Elsevier, vol. 54(1), pages 7-22, September.
    2. George B. Dantzig & Philip Wolfe, 1960. "Decomposition Principle for Linear Programs," Operations Research, INFORMS, vol. 8(1), pages 101-111, February.
    3. Silva, Marcos Melo & Subramanian, Anand & Vidal, Thibaut & Ochi, Luiz Satoru, 2012. "A simple and effective metaheuristic for the Minimum Latency Problem," European Journal of Operational Research, Elsevier, vol. 221(3), pages 513-520.
    4. Park, Junhyuk & Kim, Byung-In, 2010. "The school bus routing problem: A review," European Journal of Operational Research, Elsevier, vol. 202(2), pages 311-319, April.
    5. R. Baldacci & E. Hadjiconstantinou & A. Mingozzi, 2004. "An Exact Algorithm for the Capacitated Vehicle Routing Problem Based on a Two-Commodity Network Flow Formulation," Operations Research, INFORMS, vol. 52(5), pages 723-738, October.
    6. Guy Desaulniers & François Lessard & Ahmed Hadjar, 2008. "Tabu Search, Partial Elementarity, and Generalized k -Path Inequalities for the Vehicle Routing Problem with Time Windows," Transportation Science, INFORMS, vol. 42(3), pages 387-404, August.
    7. Roberto Baldacci & Paolo Toth & Daniele Vigo, 2010. "Exact algorithms for routing problems under vehicle capacity constraints," Annals of Operations Research, Springer, vol. 175(1), pages 213-245, March.
    8. Zeger Degraeve & Linus Schrage, 1999. "Optimal Integer Solutions to Industrial Cutting Stock Problems," INFORMS Journal on Computing, INFORMS, vol. 11(4), pages 406-419, November.
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