关键词: 蚁群算法, 参数优化, 信息素, 变异特征

Abstract: Ant colony algorithm is a novel simulated evolutionary algorithm which can provide a new way of thinking for solving complex combinatorial optimization problems. But the basic ant colony algorithm is of slow convergence and easy-to-stagnation, and easily converges to local solutions. Several optimization strategies proposed in this paper can improve several aspects of selection strategy, local search and pheromone modification to make the algorithm not easy to run into local optimal solution, and can quickly converge to the global optimal solution. Experimental results show that the modified strategies are more reasonable, effective and accurate.

Key words: ant colony algorithm, parameter optimization, pheromone, variation