求解高维复杂优化问题的改进人工蜂群算法  

Improved artificial bee algorithm for high dimensional complex optimization problems

作　　者：贺桂娇[1] 周树亮 冯冬青[2] HE Guijiao;ZHOU Shuliang;FENG Dongqing(Guangzhou Modern Information Engineering College,Guangzhou 510663,China;School of Electrical Engineering,Zhengzhou University,Zhengzhou 450001,China3.China Railway Engineering Equipment Group Co.,Ltd.,Zhengzhou 450016,China)

机构地区：[1]广州现代信息工程职业技术学院,广州510663 [2]郑州大学电气工程学院,郑州450001 [3]中国中铁工程装备集团有限公司,郑州450016

出　　处：《计算机工程与应用》2018年第12期126-132,共7页Computer Engineering and Applications

基　　金：国家自然科学基金(No.61473266);河南省重点科技攻关项目(No.152102210036)

摘　　要：为了提高人工蜂群算法求解高维复杂优化问题的能力,提出一种改进人工蜂群算法(artificial bee colony algorithm with attractor,BAABC)。在观察蜂阶段,BAABC算法摒弃轮盘赌选择策略,并通过引进吸引子改变观察蜂的搜索方式。首先,全局最优解波动产生吸引子。然后,观察蜂以吸引子为中心等比例收缩,共同开发同一区域,从而提高了算法的开发能力。实验结果表明,BAABC开发能力显著增强。关于迭代次数和时间,收敛速度都明显提高。在解决高维复杂优化问题方面,BAABC算法优势明显。值得一提的是,BAABC算法的收敛效果与问题维数无关,具有很好的鲁棒性。To solve the low capacity for high dimensional complex optimization problems, an improved artificial bee colony（BAABC）is proposed in this paper. In the stage of onlooker bees, BAABC algorithm has abandoned Roulette strategy which method onlooker bees selected nectar by, and the search way is changed for onlooker bees by introducing attractor.The attractor is generated by disturbing the global optimal solution. All onlooker bees move toward to the attractor in the same proportion. All onlooker bees together exploit the same area. So the exploitation capacity is enhanced. Experimental results show that the exploitation capacity of global search is remarkably enhanced. About the iteration number or time, convergence speed are improved obviously. To solve high dimensional complex optimization problem, the advantage of BAABC algorithm is obvious. What is more, the convergence performance of BAABC algorithm has nothing to do with the dimension of problem, and the robustness of BAABC is very strong.

关 键 词：观察蜂改进 改进算法 吸引子 高维复杂优化 轮盘赌 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]