Clustering processing ant colony algorithm

Contrary to TSP with clustering features, clustering processing ant colony algorithm (CPACA) is studied in this paper. CPACA first clusters cities in TSP, the TSP problem is decomposed into many small-scale sub-problems (the number of sub-problems equals to the clustering number of cities), then each sub-problem is solved using the ant colony algorithm in parallel, and solutions for all sub-problems are to be merged into the solution to solve the problem according to certain rules. As the problem is decomposed using the clustering characteristics of the problem itself, to solve each sub-problem in parallel, then to speed up the solving speed greatly.