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针对人工蜂群算法存在收敛速度慢、易早熟等缺点,提出一种改进的人工蜂群算法.利用随机动态局部搜索算子对当前的最优蜜源进行局部搜索,以加快算法的收敛速度;同时,采用基于排序的选择概率代替直接依赖适应度的选择概率,维持种群的多样性,以避免算法出现早熟收敛.对标准测试函数的仿真实验结果表明,所提出的算法具有较快的收敛速度和较高的求解精度.
Aiming at the shortcomings of artificial bee colony algorithm, such as slow convergence rate and premature ripening, an improved artificial bee colony algorithm is proposed to search the current optimal honey source by using a random dynamic local search operator to speed up the convergence of the algorithm. Simultaneously , The selection probability based on ranking is used instead of the selection probability directly dependent on fitness to maintain the diversity of the population so as to avoid the premature convergence of the algorithm.Experimental results of the standard test function show that the proposed algorithm has faster convergence rate and Higher solution accuracy.