Akademik Veri Yönetim Sistemi
15. International Scientific Research Congress (UBAK), Ankara, Türkiye, 17 - 18 Aralık 2022, ss.104
The traveling salesman problem (TSP) is an optimization problem in which the salesman starts from one city and must travel to all other cities in the shortest possible path. TSP is a very famous problem in the world of optimization, which is used to test the performance of new algorithms developed in this field. In this article, we investigate the traveling salesman problem using the mutation approach in the meta-heuristic algorithm of particle swarm optimization (PSO). First, we run the traveling salesman problem (for 20 cities) using the particle swarm optimization algorithm and without using the mutation operator, as a result of which we get the cost value of 455.5284. Then we use the particle swarm optimization algorithm with the mutation approach to three different methods of swap, reversion, and insertion, as a result of which the cost value obtained is 379.6574, 342.155, and 366.8056, respectively. By examining the obtained results, the particle swarm optimization method with the reversion mutation approach for solving the traveling salesman problem has the best results compared to other methods.