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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
