Genetic Algorithm-based TSP Algorithm

To address the Traveling Salesman Problem (TSP), through research, it has been found that genetic algorithms exhibit promising effectiveness in solving the TSP. Therefore, this paper adopts a genetic algorithm. It involves encoding, initializing the initial population, constructing a fitness function to guide the population towards higher fitness levels, and utilizing selection, crossover, and mutation - three operations mimicking natural biological evolution - to create new populations iteratively, continuously generating solutions for the TSP. The direction of solutions is controlled by the fitness function, aiming to solve the TSP effectively. Finally, through experiments, this paper verifies that solving the TSP using genetic algorithms yields better results in terms of finding the shortest path compared to traditional dynamic programming methods. Moreover, the paths obtained are non-overlapping, ensuring satisfactory solution paths.