关键词: 旅行商问题, 蚁群算法, 信息素, 分散度

Abstract: To settle the contradictory between convergence speed and precocity and stagnation in ant colony algorithm, an ant colony algorithm, which is based on adaptive selection of the paths and dynamic updating of pheromone, is presented. By dynamically adjusting the strategy of selection of the paths and the strategy of the trail information updating according to the distribution of the solutions, the algorithm can keep good balance between accelerating convergence and averting precocity and stagnation. Experimental results on traveling salesman problem show that the method presented in this paper has a better global searching ability, higher convergence speed and solution diversity than that of classical ant colony algorithm.

Key words: traveling salesman problem, ant colony algorithm, pheromone, dispersed degree