Solving TSP with Characteristic of Clustering by Ant Colony Algorithm

Ant colony algorithm (ACA) is a novel simulated evolutionary algorithm which was proposed in recent years. Preliminary study has shown that the algorithm is very robust and has great capabilities in searching better solution, but at the same time there are some shortcomings such as converging slowly in the algorithm. To tackle traveling salesman problem (TSP) with characteristic of clustering, a new ACA algorithm is proposed. First the TSP problem is divided into several sub-problems by clustering processing, and then all the sub-problems will be solved in parallelization by ACA algorithm, respectively. At last all the solutions of each sub-problem will be merged into the solution of the TSP problem by some rules. Simulated experiment on TSP with characteristic of clustering shows that the convergence rate of the new algorithm has been greatly improved.