An Improved Ant Colony Optimization for the Vehicle Routing Problem in Logistics Distribution

Abstract

The routing of a fleet of vehicles to service a set of customers is important in logistic distribution systems. The main objective of Vehicle routing problem (VRP) is to minimize the total required fleet size for serving all customers. Secondary objectives are to minimize the total distance traveled or to minimize the total route duration of all vehicles. In this paper, we present a hybrid ant colony System, named PACS, coupled with a pareto local search (PLS) algorithm and apply to the VRP and its variant, the VRP with Time Windows (VRPTW). The algorithm only chooses partial customers randomly to compute the transition probability and PLS can help to escape local optimum. Experiments on various aspects of the algorithm and computational results for some benchmark problems are reported. We compare our approach with some classic, powerful meta-heuristics and show that the proposed approach can obtain the better quality of the solutions.