具有混沌差分进化搜索的人工蜂群算法

摘要

针对人工蜂群算法的不足,结合差分进化算法中的变异思想,提出一种改进的人工蜂群算法.其基本思想是在标准人工蜂群算法中观察蜂更新蜜源的阶段,使用差分进化算子对蜜源进行更新,在差分变异算子中引入混沌序列,以提高观察蜂在此阶段的局部搜索能力,最终获得最优蜜源.仿真结果表明,引入混沌差分进化搜索的蜂群算法无论在解的求解精度上还是算法的收敛速度上均优于标准人工蜂群算法,适合于复杂函数的全局优化问题.%An improved Artificial Bee Colony (ABC) algorithm is proposed to overcome the shortcomings of standard ABC by combining with differential mutation idea. Its main idea is that the proposed algorithm makes use of differential evolution operators to update food source in order to enhance the local search ability at the stage of onlooker bees,and the chaotic se quence is introduced to differential mutation operator.Simulation results show that the new algorithm introducing chaotic dif ferential evolution search is promising in terms of convergence rate and has great advantage of solution accuracy compared to ABC algorithm.The improved algorithm can be efficiently employed to complex functions of global optimization problems.