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VRP 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 rout crossover techniques and swap mutation procedure is used respectively. In this paper, the authors focus on two objectives of VRP, i.e., number of vehicles and total cost (distance).The proposed MOGA finds optimum solutions effectively.
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