A columnar competitive model for solving multi-traveling salesman problem

This paper studies an optimization problem: multi-traveling salesman problem (MTSP), which is an extension of the well known TSP. A columnar competitive model (CCM) of neural networks incorporates with a winner-take-all learning rule is employed to solve the MTSP. Stability conditions of CCM for MTSP is exploited by mathematical analysis. Parameters settings of the network for guaranteeing the network converges to valid solutions are discussed in detail. Simulations are carried out to illustrate the performance of the columnar competitive model compare to the heuristic algorithms: Tabu Search.