混合排名映射概率和混沌搜索的ABC算法  

Artificial Bee Colony Algorithm Based on Hybrid Rank Mapping Probability and Chaotic Search

作　　者：张新明[1] 魏峰[1] 牛丽平[1] 王鲜芳[1] 

机构地区：[1]河南师范大学计算机与信息工程学院,新乡453007

出　　处：《计算机科学》2014年第2期102-106,144,共6页Computer Science

基　　金：国家自然科学基金(61173071);河南省重点科技攻关项目(092102210017)资助

摘　　要：针对由于人工蜂群算法(Artificial Bee Colony algorithm,ABC)采用直接映射概率选择食物源而引起收敛速度慢、陷入局部最优等问题,提出一种混合排名映射概率和混沌搜索的人工蜂群算法((Artificial Bee Colony algorithm based on Hybrid rank mapping probability and Chaotic search,ABC-HC))。首先,利用目标函数值的排名来获取选择食物源的排名映射概率,并提出计算排名映射概率的两种方法;然后,在观察蜂阶段,融合这两种计算概率的方法,即不同的搜索阶段采用不同的排名映射方法计算食物源选择概率,构造基于混合排名映射概率的人工蜂群算法,以便能够维持种群的多样性避免陷于局部最优;最后,在侦查蜂阶段,使用混沌搜索替代随机搜索以便进一步提高收敛速度,最终获得较好的全局最优解。对10个标准测试函数进行仿真,结果表明,ABC-HC算法不仅提高了收敛速度,而且更能跳出局部最优,有效地找到全局最优解,优于标准的ABC算法和进化算法。In view of the shortcomings of arti^icial bee colony algorithms, such as the low convergence rate and being trapped into local optimums owing to choosing the food source based on direct mapping probability, an Artificial Bee Colony optim^ation algorithm based on Hybrid rank mapping probability and Chaotic search （ABC-HC） was proposed in this paper. First, two computing probability method to choose food sources were created based on rank mapping. Then the ABC algorithm based on combining the two probability methods in a onlooker bee phrase was proposed in order to keep diversities of the solutions and not to be trapped into local optimums. Finally, in a scout bee phrase, random search was replaced with chaotic search to get a higher convergence rate and a global solution effectively. The simulation results on 10 standard test complicated functions indicate that the proposed optimization algorithm is rapid and effective and outperforms the standard ABC algorithm and the evolutionary ones.

关 键 词：人工蜂群算法 排名映射概率 直接映射概率 混沌搜索 随机搜索 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]