关键词: 蚁群算法, 粒子群算法, 模糊技术, 群体智能, 演化交叉

Abstract: In order to solve the complex scale problem of traveling salesman, it puts forward a kind of swarm intelligent hybrid algorithm of combination of ant colony algorithm and particle swarm algorithm and constructs fuzzy self-adapted adjustment model of inertia weight. For the hybrid algorithm trapped into local optimaleasily, the parameter automatic adjustment mechanism is designed to achieve local search and global search of equilibrium. In the early of search, the parameters [ω] would adaptively adjust to a larger value, after that the algorithm has strong global search ability. In the late stage of search, the parameters [ω] would adaptively adjust to a smaller value, after that the algorithm has strong local search capability. A number of simulation experiments show that search ability of the improved hybrid algorithm is superior to the similar algorithm and traditional algorithm. And it has satisfactory results applied in large scale TSP.

Key words: ant colony algorithm, particle swarm algorithm, fuzzy technology, swarm intelligence, evolution cross