Research on TSP Solution Based on Genetic Algorithm

Genetic algorithm has been widely used in many fields because of its good global search capability. In this paper, we mainly introduce the research on Traveling Salesman Problem (TSP) solution in 26 cities based on genetic algorithm. We adopt tournament selection, order insert crossover and exchange mutation methods to solve this problem. However, it does not perform sufficiently well enough, so we optimize the operators by using elitist selection and inversion mutation methods. With the improved operators, we can prevalent the shortcomings of traditional genetic algorithm, prevent convergence into a local optimum, guarantee the stability of population evolution, dismantle cross paths and finally find the optimal solution. The obtained information is useful for further genetic algorithm parameters, operators settings and practical problems.