基于非线性递减选择策略的人工蜂群算法

Artificial Bee Colony Algorithm Based on Nonlinear Decreasing Selection Strategy

针对基本人工蜂群算法种群多样性难以保持,进化速度慢等问题,提出了一种基于非线性递减选择策略的人工蜂群算法。算法在雇佣蜂阶段采用非线性递减选择策略以提高种群的多样性,进而改善种群的全局勘探能力;在跟随蜂阶段由全局最优解引导搜寻新解,以提高种群的局部开发能力;侦察蜂采用贴近最优解的策略以提高生成新解的质量,加速种群进化。改进的三个阶段改善了算法的寻优性能,最后通过实验对比与分析,验证了该算法的有效性。

An artificial bee colony algorithm based on nonlinear decreasing selection strategy is proposed to solve the prob⁃lems of population diversity and slow evolution of basic artificial bee colony algorithm.The algorithm adopts the nonlinear decreasing selection strategy to improve the diversity of the population and improve the global exploration ability of the population.In the follow⁃ing stage,the global optimal solution is used to guide the search for new solutions to improve the local development ability of the population.The scout bee adopts the strategy close to the optimal solution to improve the quality of the new solution and accelerate the population evolution.In the three stages,the optimization performance of the algorithm is improved.Finally,the effectiveness of the algorithm is verified by experimental comparison and analysis.