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A Pattern Mining Heuristic for the Extension of Multi-trip Vehicle Routing

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Optimization, Learning Algorithms and Applications (OL2A 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1981))

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Abstract

Multi-trip vehicle routing problem with a variable number of wagons significantly reduces the number of vehicles and drivers needed to service customers. It is often hard to solve these problems in acceptable CPU times using exact algorithms when the problem contains very big real-world data sets. We use meta-heuristic algorithms to get a solution close to the optimal solutions for vehicle routing problems with a dynamic capacity of a vehicle. First, local search heuristics applied with genetic algorithms are proposed. Then, a pattern-mining algorithm is developed to improve the solutions found from the genetic algorithm. We perform detailed experiments on Solomon instances for vehicle routing problem with time windows (VRPTW). Our experiments establish the effectiveness of the algorithms.

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Authors and Affiliations

  1. School of Computing, Queen’s University, Kingston, ON, K7L 3N6, Canada

    Leila Karimi, Connor Little & Salimur Choudhury

Authors
  1. Leila Karimi
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  2. Connor Little
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  3. Salimur Choudhury
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Corresponding author

Correspondence to Connor Little .

Editor information

Editors and Affiliations

  1. Instituto Politécnico de Bragança, Bragança, Portugal

    Ana I. Pereira

  2. University of Azores, Ponta Delgada, Portugal

    Armando Mendes

  3. Instituto Politécnico de Bragança, Bragança, Portugal

    Florbela P. Fernandes

  4. Instituto Politécnico de Bragança, Bragança, Portugal

    Maria F. Pacheco

  5. Instituto Politécnico de Bragança, Bragança, Portugal

    João P. Coelho

  6. Instituto Politécnico de Bragança, Bragança, Portugal

    José Lima

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Karimi, L., Little, C., Choudhury, S. (2024). A Pattern Mining Heuristic for the Extension of Multi-trip Vehicle Routing. In: Pereira, A.I., Mendes, A., Fernandes, F.P., Pacheco, M.F., Coelho, J.P., Lima, J. (eds) Optimization, Learning Algorithms and Applications. OL2A 2023. Communications in Computer and Information Science, vol 1981. Springer, Cham. https://doi.org/10.1007/978-3-031-53025-8_6

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  • DOI: https://doi.org/10.1007/978-3-031-53025-8_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-53024-1

  • Online ISBN: 978-3-031-53025-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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