An Ant Colony Optimization Algorithm with Variable Neighborhood Search for Vehicle Routing Problems with Time Windows on Road Networks

This article addresses the vehicle routing problem with time windows (VRPTW) based on real road networks, considering the speed limit and transportation cost attributes on the road networks. In this paper, an ant colony optimization algorithm with variable neighborhood search (ACO-VNS) is proposed to solve VRPTW on road networks, in which the ACO pheromone convergence mechanism is beneficial to improve the convergence speed, while the VNS can be used to prevent the ACO from falling into the local optimal solution and improve the quality of the final solution. In this paper, 15 test sets are generated based on the information of the real road network in Nanshan District, Shenzhen. The comparison experiments on the test sets show that the algorithm can effectively obtain better solutions.