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A p-step formulation for the capacitated vehicle routing problem

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  • Dollevoet, T.A.B.
  • Munari, P.
  • Spliet, R.

Abstract

We introduce a _p_-step formulation for the capacitated vehicle routing problem (CVRP). The parameter _p_ indicates the length of partial paths corresponding to the used variables. This provides a family of formulations including both the traditional arc-based and path-based formulations. Hence, it is a generalization which unifies arc-based and path-based formulations, while also providing new formulations. We show that the LP bound of the _p_-step formulation is increasing in _p_, although not monotonically. Furthermore, we prove that computing the set partitioning bound is NP-hard. This is a meaningful result in itself, but combined with the _p_-step formulation this also allows us to show that there does not exist a strongest compact formulation for the CVRP, if _P ≠ NP_. While ending the search for a strongest compact formulation, we propose the search for the strongest formulation of the CVRP with a number of variables and constraints limited by a polynomial of fixed degree. We provide new strongest such formulations of degree three and higher by using a corresponding _p_-step formulation. Furthermore, the results of our experiments suggest that there are computational advantages from using the _p_-step formulation, instead of traditional arc-based and path-based formulations.

Suggested Citation

  • Dollevoet, T.A.B. & Munari, P. & Spliet, R., 2020. "A p-step formulation for the capacitated vehicle routing problem," Econometric Institute Research Papers EI2020-01, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  • Handle: RePEc:ems:eureir:123411
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    References listed on IDEAS

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    1. Gouveia, Luis, 1995. "A result on projection for the vehicle routing ptoblem," European Journal of Operational Research, Elsevier, vol. 85(3), pages 610-624, September.
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    3. Roberto Baldacci & Aristide Mingozzi & Roberto Roberti, 2011. "New Route Relaxation and Pricing Strategies for the Vehicle Routing Problem," Operations Research, INFORMS, vol. 59(5), pages 1269-1283, October.
    4. 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.
    5. Martinelli, Rafael & Pecin, Diego & Poggi, Marcus, 2014. "Efficient elementary and restricted non-elementary route pricing," European Journal of Operational Research, Elsevier, vol. 239(1), pages 102-111.
    6. 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.
    7. Leggieri, Valeria & Haouari, Mohamed, 2017. "Lifted polynomial size formulations for the homogeneous and heterogeneous vehicle routing problems," European Journal of Operational Research, Elsevier, vol. 263(3), pages 755-767.
    8. Mads Jepsen & Bjørn Petersen & Simon Spoorendonk & David Pisinger, 2008. "Subset-Row Inequalities Applied to the Vehicle-Routing Problem with Time Windows," Operations Research, INFORMS, vol. 56(2), pages 497-511, April.
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    Cited by:

    1. Dollevoet, T.A.B. & Pecin, D. & Spliet, R., 2020. "The path programming problem and a partial path relaxation," Econometric Institute Research Papers EI-2020-04, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Twan Dollevoet & Remy Spliet, 2023. "Preprocessing to Reduce Vehicle Capacity for Routing Problems," SN Operations Research Forum, Springer, vol. 4(2), pages 1-7, June.

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