Iterated variable neighborhood descent algorithm for the capacitated vehicle routing problem

摘要

The capacitated vehicle routing problem (CVRP) aims to determine the minimum total cost routes for a fleet of homogeneous vehicles to serve a set of customers. A wide spectrum of applications outlines the relevance of this problem. In this paper, a hybrid heuristic method IVND with variable neighborhood descent based on multi-operator optimization is proposed for solving the CVRP. A perturbation strategy has been designed by cross-exchange operator to help optimization escape from local minima. The performance of our algorithm has been tested on 34 CVRP benchmark problems and it shows that the proposed IVND performs well and is quite competitive with other state-of-the-art heuristics. Additionally, the proposed IVND is flexible and problem dependent, as well as easy to implement.