【摘要】 针对无约束优化问题,提出一种新颖的混沌人工蜂群算法。新算法在Memetic算法框架的基础上,采用人工蜂群算法作为全局搜索算法,采用混沌搜索算子作为局部搜索算法。为了进一步提升算法的开采能力,新算法的侦察蜂抛弃了随机生成新食物源的方法,采用针对陷入局部极值食物源进行混沌局部搜索生成候选食物源的方式。针对五个标准Benchmark函数的仿真实验结果显示,与标准人工蜂群算法相比,新算法求解精度具有一定优势。更多还原

【Abstract】 This paper proposed novel chaos-artificial bee colony algorithm for continuous function optimization problems.Based on the Memetic algorithm framework,the new algorithm took artificial bee colony algorithm as the global search algorithm and the chaos local search operator as the local search operator algorithm.Furthermore,for the food source which was into local minimum,the scout didn’t randomly generate the new food source,but used the chaos local operator to generate the candidate food source in order to enhance the exploit of bee colony.The simulation results for five Benchmark functions show that,compared with those of artificial bee colony algorithm,the new algorithm has the advantages to the solutions’ quality.更多还原