Multi Objective Genetic Approach for Solving Vehicle Routing Problem with Time Window

Vehicle routing problem with time window (VRPTW) is a NP-Complete and a multi-objective problem. The problem involves optimizing a fleet of vehicles that are to serve a number of customers from a central depot. Each vehicle has limited capacity and each customer has a certain demand. Genetic Algorithms maintain a population of solutions by means of a crossover and mutation operators. For crossover and mutation, best cost route crossover techniques and exchange mutation procedure is used respectively. In this paper, we focus on three objectives of VRPTW i.e. number of vehicles, total cost (distance), and time window violation (routing time). The proposed Multi Objective Genetic Algorithm (MOGA) finds optimum solutions effectively.