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VRPSolverEasy: A Python Library for the Exact Solution of a Rich Vehicle Routing Problem

Author

Listed:
  • Najib Errami

    (Inria Centre of the University of Bordeaux–Sud-Ouest, 33405 Talence, France)

  • Eduardo Queiroga

    (Inria Centre of the University of Bordeaux–Sud-Ouest, 33405 Talence, France)

  • Ruslan Sadykov

    (Inria Centre of the University of Bordeaux–Sud-Ouest, 33405 Talence, France)

  • Eduardo Uchoa

    (Inria Centre of the University of Bordeaux–Sud-Ouest, 33405 Talence, France; Universidade Federal Fluminense–Engenharia de Produção, Niterói 24210-240, Brazil)

Abstract

The optimization community has made significant progress in solving vehicle routing problems (VRPs) to optimality using sophisticated branch-cut-and-price (BCP) algorithms. VRPSolver is a BCP algorithm with excellent performance in many VRP variants. However, its complex underlying mathematical model makes it hardly accessible to routing practitioners. To address this, VRPSolverEasy provides a Python interface to VRPSolver that does not require any knowledge of mixed integer programming modeling. Instead, routing problems are defined in terms of familiar elements, such as depots, customers, links, and vehicle types. VRPSolverEasy can handle several popular VRP variants and arbitrary combinations of them.

Suggested Citation

  • Najib Errami & Eduardo Queiroga & Ruslan Sadykov & Eduardo Uchoa, 2024. "VRPSolverEasy: A Python Library for the Exact Solution of a Rich Vehicle Routing Problem," INFORMS Journal on Computing, INFORMS, vol. 36(4), pages 956-965, July.
    • Handle: RePEc:inm:orijoc:v:36:y:2024:i:4:p:956-965
    DOI: 10.1287/ijoc.2023.0103
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