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A multiple ant colony system with random variable neighbourhood descent for the vehicle routing problem with time windows

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  • Orivalde S. Silva Júnior
  • José E. Leal

Abstract

This paper proposes hybrid heuristics that use the multiple ant colony system (MACS) and random variable neighbourhood descent (RVND) algorithms to solve the vehicle routing problem with time windows (VRPTW). This problem involves determining the minimum-cost routes for a fleet of vehicles of the same capacity to visit a set of customers within a specified time interval, called a time window. The proposed heuristic, called MACS-RVND, uses two ant colonies to reduce the number of vehicles and the total distance travelled, and a RVND algorithm is used in the local search procedure. The algorithm was tested using standard benchmark problems in the literature and produced competitive results. The use of the RVND algorithm improved the MACS-VRPTW algorithm.

Suggested Citation

  • Orivalde S. Silva Júnior & José E. Leal, 2021. "A multiple ant colony system with random variable neighbourhood descent for the vehicle routing problem with time windows," International Journal of Logistics Systems and Management, Inderscience Enterprises Ltd, vol. 40(1), pages 52-69.
    • Handle: RePEc:ids:ijlsma:v:40:y:2021:i:1:p:52-69
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    Cited by:

    1. Wang, Jianxin & Lim, Ming K. & Liu, Weihua, 2024. "Promoting intelligent IoT-driven logistics through integrating dynamic demand and sustainable logistics operations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 185(C).

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