Comparative Approach of Computational Models Applied to the Traveling Salesman Problem: A Case Study Performed at Tourist Points in the Ibiapaba Mountains, CE, Brazil

The region of Ibiapaba mountains, in Ceará, stands out as a region with excellent tourist potential in the state. Due to this, the present paper carried out comparative tests between four algorithms to solve the Traveling Salesman Problem applied to tourist places in the region. The general objective is to verify which of the algorithms obtained the best performance, measured through the execution time, to find an optimal route between a set of tourist sites. The studied algorithms were Brute Force, Ant Colony Optimization, Genetic Algorithm, and 2-OPT algorithm. We modeled the Traveling Salesman Problem using graphs and distances and captured real locations using Google Maps. The results showed the faster 2-OPT algorithm during tests, although any of the tested algorithms can perform this function, depending on the number of points of interest. This work is a basis for future optimized tourist itinerary planner applications.