Traveling Salesman Problem via Swarm Intelligence

Traveling Salesman Problem (TSP) is one of the most classic combinatorial optimization problems. It can be widely applied in many real-world applications. In this paper, we propose an efficient method via swarm intelligence to handle the traveling salesman problem, which may not be suitable for the standard particle swarm optimization due to its domain’s discrete nature. Compared to the classic Ant Colony Optimization method, the SIB method performs well in terms of efficiency and accuracy in the TSP problem. For TSP with cities size between 15 to 25, SIB has a significantly lower average executing time to obtain an adequate solution with close distance.