This project proposes a comparative analysis of three metaheuristic algorithms, namely Simulated Annealing, Genetic Algorithm, and Ant Colony Optimization, for solving the Traveling Salesman Problem with 107 cities. The objective is to determine which algorithm can provide the best solution in terms of computational efficiency and solution quality. The algorithms are implemented and tested using a dataset of 107 cities. The findings of these algorithms will be used to determine the most optimal solution for the Traveling Salesman Problem among them.

Language Used:

• Java