Ant Colony Algorithm Approach for Solving Traveling Salesman with Multi-agent

Traveling Salesman Problem is a very classical optimization problem in the field of operations research, and often-used benchmark for new optimization techniques. This paper will to bring up multi-agent approach for solving the Traveling Salesman Problem based on data mining algorithm, for the extraction of knowledge from a large set of Traveling Salesman Problem. The proposed approach supports the distributed solving to the Traveling Salesman Problem. It divides into three-tier, the first tier is ant colony optimization agent; the second-tier is genetic algorithm agent; and the third tier is fast local searching agent. In using an Ant Colony Algorithm for the Traveling Salesman Problem, An attribute-oriented induction methodology was used to explore the relationship between an operations´ sequence and its attributes and a set of rules has been developed. These rules can duplicate the Ant Colony Algorithm performance on identical problems. Ultimately, the experimental results have shown that the proposed hybrid approach has good performance with respect to the quality of solution and the speed of computation.