基于轮盘赌反向选择机制的蜂群优化算法  

Artificial bee colony based on reverse selection of roulette

作　　者：向万里[1,2] 马寿峰[1] 

机构地区：[1]天津大学系统工程研究所,天津300072 [2]兰州交通大学交通运输学院,兰州730070

出　　处：《计算机应用研究》2013年第1期86-89,共4页Application Research of Computers

基　　金：国家自然科学基金资助项目(70971094);天津市科技支撑计划基金资助重点项目(08ZCKFSF01000);高等学校博士学科点专项科研基金资助项目(20090032110033)

摘　　要：针对人工蜂群算法易陷入局部最优的不足,考虑到基本蜂群算法中个体选择大多基于贪婪选择的思想,从而使算法快速向适应度值高的个体进化而陷入局部停滞。为此,提出一种基于轮盘赌的反向选择机制,以保持蜂群个体的多样性而使算法保持较好进化能力。通过对经典测试函数的仿真实验表明,改进的蜂群算法有更快的收敛速度和更好的收敛精度,且改进的蜂群算法对群体规模有很强的鲁棒性。Towards the defect which inclined artificial bee colony（ABC） to fall into local minima,and taking into account of greedy selection scheme was always employed during the basic artificial bee colony,which resulted in rapid evolving toward the more fitter individual,and thus trapped the ABC into stagnation.Thus,this paper proposed a modified artificial bee colony（MABC） based on reverse selection of roulette which retaining the diversity of population in order to improve the evolving capability.Experiments result on a few of benchmark functions show that the MABC algorithm not only effectively avoids the premature convergence,but also significantly improves the convergence speed and the convergence precision.Moreover,the MABC algorithm is robust to the scale of population.

关 键 词：人工蜂群算法 轮盘赌选择 反向选择 鲁棒性 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]