Solution to the TSP Problem Based on the Improved Ant Colony Algorithm

Traveling Salesman Problem (TSP) is one of the typical combinatorial optimization problems. Compared with closed-loop TSP problems, non-closed-loop TSP problems are more common in actual production processes such as logistics distribution and route planning. However, the traditional ant colony algorithm tends to converge to the local optimal solution when solving the non-closed-loop TSP problem, and is more sensitive to the changes of environmental factors. This study adopts a new type of adaptive and improved ant colony system to analyze and solve the non-closed-loop TSP problem. An adaptive mechanism incorporating pheromone weighting, heuristic influence, and pheromone evaporation factors is introduced to enhance the ant colony algorithm. The performance of both the standard and enhanced algorithms is evaluated on complex TSP instances, with simulation results confirming the effectiveness of the proposed improvements.