^{1}and K. Vivekanandan

^{2}

^{1}Department of MCA, Sri ManakulaVinayagar Engineering College, Puducherry, India.

^{2}Department of Computer Scienceand Engineering, Pondicherry Engineering College, Puducherry, India.

This paper depicts, a solution model for solving Capacitated Vehicle Routing Problem using Genetic Algorithm. The solution of classical Capacitated Vehicle Routing Problem (CVRP) is a set of vehicles which all start and end in the depot, and which satisfies the constraint that the set of customers/cities has to be visited exactly once with minimal cost with the additional constraint that every vehicle must have uniform capacity of a single commodity. The Genetic Algorithms (GA) are direct, stochastic method for global search and optimization, which generate solutions to the optimization problems using techniques inspired by natural evolution, such as inheritance, mutation, selection, and cross over. The CVRP is a combinatorial optimization problem in which initial population plays an imperative function in finding the optimal solution. To find the initial population, a novel Ordered Distance Vector (ODV) based Equi-begin with Variable diversity (EV) technique is implemented.The CVRP problem involves optimizing a fleet of vehicles that are to serve number of customers from a central depot. Each vehicle has limited capacity and each customer has a certain demand. The objective is to minimize the vehicle fleet, the sum of travel time, and the total demand of commodities for each route may not exceed the capacity of the vehicle which serves that route.Computational results arecarriedoutusingthe CVRPbenchmarkinstancesobtainedfromtheVRPLIB were experimented using MATLAB software. The experimental results for the proposed technique is compared with the Gene Bank population seeding technique and found that the proposed EV technique gives the best convergence and diversity than the Gene Bank population seeding technique. The experiment based on the other performance factors are analysed such that EV techniques gives the best solutions in terms of convergence rate, error rate, convergence diversity and computation time for a Capacitated Vehicle Routing Problems.