计算机工程与应用Issue(23)：51-55,5.DOI:10.3778/j.issn.1002-8331.1305-0076
基于搜索能力均衡的人工蜂群算法
Improved artificial bee colony algorithm based on balance of searching ability
摘要
Abstract
In view of the defect that Artificial Bee Colony(ABC)algorithm is poor at exploitation, an Improved Artificial Bee Colony(IABC)algorithm is proposed based on two new solution search strategies. A new solution search equation, in which the other individual can be driven under the guidance of the best individual with best fitness value, is introduced so as to improve the capability of exploitation. To achieve a good tradeoff between the exploitation and exploration, a new random item is integrated into the original solution search equation to enhance the ability of exploration on the onlooker bee phase of ABC. To further balance the ability of exploration and exploitation, some modifications are done on the scout bee phase of ABC. In order to validate the convergence performance of IABC, experiments tested on twelve benchmark functions are conducted. And the experimental results show that the convergence performance of IABC is enhanced conspicuously.关键词
人工蜂群算法/搜索方程/全局探索/局部开发/均衡Key words
artificial bee colony algorithm/solution search equation/global exploration/local exploitation/tradeoff分类
信息技术与安全科学引用本文复制引用
向万里,安美清,何瑞春,张静芳,马昌喜..基于搜索能力均衡的人工蜂群算法[J].计算机工程与应用,2014,(23):51-55,5.基金项目
国家自然科学基金（No.61064012，No.61164003）；兰州交通大学青年科学基金（No.2012029）；兰州交通大学科技支撑基金（No.ZC2014010）。 （）
