A Comparative Study of solving Traveling Salesman Problem with Genetic Algorithm, Ant Colony Algorithm, and Particle Swarm Optimization

To solve the problem of traveling salesman (TSP), some intelligent optimization algorithms such as genetic algorithm (GA), ant colony algorithm (ACO), and particle swarm optimization (PSO) algorithm were used. This paper attempts to discuss the optimal solutions and convergence speed change of the three algorithms in solving the problem. We conducted a simulation experiment, found that the PSO provided a better and more stable solution, ACO took the shortest running time and GA is less influenced by the problem scale.