Genetic algorithm based approach for vehicle routing problem with time windows

Logistics and supply chain management deals with managing the flow of goods from suppliers, through its facilities, and on to its customers. It is of critical importance in establishing a competitive advantage. Proper performance of the logistics functions can contribute to both lower costs and to enhance customer service. To reduce transportation costs and also to improve customer service, finding the best paths for vehicles that will minimise time or distance is frequent decision problem and this is commonly known as the Vehicle Routing Problem. In this paper, Genetic Algorithm (GA) based heuristic is proposed to solve Vehicle Routing Problem with Time Windows. The initial population of the GA is generated using Greedy Randomised Adaptive Search Procedure. The proposed algorithm is tested with bench mark instances and is found to be better solutions than published results.