一种自适应混沌蜂群优化算法研究

Research of an Adaptive Chaotic Artificial Bee Colony Algorithm

针对人工蜂群算法在寻优后期搜索变慢、易陷入局部最优的问题,提出了一种自适应混沌蜂群算法,将混沌算法应用到蜂群的初始化和搜索后期,防止其陷入局部最优,同时提出了一种自适应步长算法,增加了算法寻优后期的搜寻速度。通过对测试函数寻优结果的对比分析验证了该算法的优越性。

To the problem of optimization search slowly lately and into the local optimal problem in artificial colony algorithm, this paper proposes an adaptive chaotic ABC algorithm. The chaos algorithm is applied to the initialization of swarm and late search, which is to prevent the fall in local optimum. An algorithm of adaptive step length is put forward to increase the search speed of opti. mization in the late. Through the contrastive analysis of test function optimization results is verified the superiority of the algorithm.