TSP Solving Utilizing Improved Ant Colony Algorithm
Abstract To solve the premature issue of TSP solving using the ant colony optimization algorithm (ACO), this paper proposes an improved ACO using particle swarm optimization (PSO) to solve the classic traveling salesman problem (TSP). The algorithm’s strategy includes three stages: firstly, establishing a mathematical model according to the optimization objective, and then solving the optimal path obtained by the particle swarm optimization algorithm. Finally, the pheromone concentration of this path in the ant colony mathematical model is enhanced according to the particle swarm optimization algorithm’s optimal path. A classic TSP case is used to compare the PSO and ACO. The results show that the proposed improved algorithm has a faster convergence speed and can converge to the optimal global solution, and its performance is better than that of ACO and PSO.