摘要
针对基本蚁群算法容易出现早熟和停滞现象的缺点,从信息素的更新策略方面对蚁群算法进行改进,自适应地调整挥发系数,提出了基于挥发系数的自适应蚁群算法。以TSP问题为例,分别用自适应蚁群算法与基本蚁群算法进行了计算,实验结果表明,该算法比一般蚁群算法具有更好的全局搜索能力和收敛速度,可以在加速收敛和防止早熟、停滞现象之间取得很好的平衡。
In accordance with the defect of early maturity and stagnation, this article, from the pheromone, updates strategy to improve on ant colony algorithm, adaptively adjusting evaporation coefficient,and proposes a new algorithm. Exampled by TSP, using adaptive and basic ant colony algorithm respectively produces experimental results showing that the algorithm is better than the average in global search ability, convergence rate and a good balance can be reached among accelerating convergence, prevention of premature, and stagnation.
出处
《福建金融管理干部学院学报》
2010年第1期54-58,共5页
Journal of Fujian Institute of Financial Administrators
关键词
蚁群算法
旅行商问题
挥发系数
Ant colony algorithm
Traveling salesman problem
Evaporation coefficient
