摘要
有关蚁群优化算法收敛性分析的研究还很少,不利于进一步改进其算法.为此,较详细地分析了用蚁群优化算法求解TSP问题的收敛性,证明了当0<q0<1时,算法能够收敛到最优解.分析了封闭路径性质、启发函数、信息素和q0对收敛性的影响,据此给出了提高算法收敛速度的几点结论.
The convergence problems of ant colony optimization algorithm is studied. To improve the algorithm, the convergence of this algorithm applied to TSP is analyzed in detail. The algorithm will be certain to converge to the optimal solution under the condition 0〈q0〈1. In addition, the influence on its convergence caused by the properties of the closed path, heuristic functions, the pheromone and q0 is analyzed. Based on it, some conclusions about the improvement of the speed of convergence are obtained.
出处
《控制与决策》
EI
CSCD
北大核心
2006年第7期763-766,770,共5页
Control and Decision
基金
江苏省自然科学基金项目(01KJB520007)
关键词
蚁群优化算法
收敛性分析
启发函数
TSP问题
Ant colony optimization algorithm
Convergence analysis
Heuristic function
Traveling salesman problem
