Hybrid Genetic Algorithm for Vehicle Routing Problem with Time Windows

Abstract

Vehicle Routing Problem (VRP) is an important class of scheduling optimization problems in the supply chain management. Vehicle Routing Problem with Time Windows (VRPTW) is an extension of VRP and involves the setoff of a fleet of vehicles from a depot to serve a number of customers at different geographic locations for within specific time windows before returning to the depot eventually. This study aims to solve VRPTW, which has received considerable attention in recent years. To solve this problem, this study suggests a hybrid genetic algorithm combined with priority rule heuristic to make an initial population and ^λ- interchange mechanism to increase the diversity of the population and enhance the local search, applying guiding mutation to find improved descendant and using the Bi-directional Decoding (BDD) to find the better solution of the same chromosome. Finally, the repairing method is applied to reduce the number of non-feasible solutions in population. Experimental results show that the proposed hybrid algorithm has a better performance than other related algorithms.