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

Orivalde S. Silva Júnior and José E. Leal

International Journal of Logistics Systems and Management, 2021, vol. 40, issue 1, 52-69

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.

Keywords: VRPTW; vehicle routing problem with time windows; metaheuristics; ant colony optimisation; ACO; random variable neighbourhood descent; RVND; delivery service. (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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