Improved multi-ant-colony algorithm for solving multi-objective vehicle routing problems

Classical Vehicle Routing Problems (VRP) involve the supply of goods/services from a central depot to geographically scattered customers. Besides the classical objective of minimizing the total traveled distance, the present work also considers simultaneous optimization of two additional objectives namely minimizing makespan and minimizing distance imbalance. A mathematical model has been developed to deal with this multi-objective version of VRP (MO-VRPTW). A meta-heuristic based on multiple ant colony systems for solving this MO-VRPTW has also been proposed. Fire y optimization Algorithm (FA) has also been applied to avoid local optima. Two new migration operators named Migration-I and Migration-II and multi-pheromone matrices have been developed to further improve the solution quality. The proposed algorithm has been tested on a number of benchmark problems and its superiority over other state-of-the-art approaches and Non Dominated Sorting Algorithm-II (NSGA-II) is demonstrated.