A dynamic max-min ant system for solving the travelling salesman problem

In this paper, a modified max-min ant system, called dynamic max-min ant system (DMAS) is proposed to solve the travelling salesman problem (TSP). The proposed algorithm updates the value of tau(min), the lower bound of pheromone trails during its run. In addition, the used parameters for the DMAS are adjusted to improve the performance of the method. Furthermore, a local search based on 2-Opt is adjoined to the DMAS and the results are reported. Moreover, the DMAS is applied to some standard TSPs and its results are compared to some previous works. Results show that the proposed method outperforms several other well-known population-based methods in many cases. Also, in some standard problems, the proposed method improves the shortest known tour lengths. Moreover, experiments show that the standard deviation of tour lengths that are found by DMAS is very small, which exhibits the stability of the proposed algorithm.