关键词: 信息素, 蚁群算法, 云模型, 旅行商问题

Abstract: To overcome the slow convergence and local extrema of ant colony algorithm, the cloud model theory is adopted to regulate reasonably the degree of randomness of the ant colony algorithm. Several adaptive strategies are proposed for the parameters of the ant colony algorithm and the cloud model, and for the optimum path determination. Meanwhile, the evaluation algorithm of pheromone distribution is proposed. Simulation results for multiple TSP validate the efficiency and stability of the proposed algorithm.

Key words: pheromone, ant colony algorithm, cloud model, traveling salesman problem