An Improved Multi-agent Approach for Solving Large Traveling Salesman Problem

The traveling salesman problem (TSP) is a very hard optimization problem in the field of operations research. It has been shown to be NP-hard, and is an often-used benchmark for new optimization techniques. This paper pro- poses an improved multi-agent approach for solving large TSP. This proposed approach mainly includes three kinds of agents with different function. The first kind of agent is conformation agent and its function is generating the new solution continuously. The second kind of agent is optimization agent and its function is optimizing the current solutions group. The third kind of agent is refining agent and its function is refining the best solution from the beginning of the trial. At same time, there are many sub-agents in each kind of agent. These sub-agents accomplish the task of its superior agent cooperatively. At the end of this paper, 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.