摘要
为快速准确地优化复杂函数,通过引入自适应竞争机制来改进基本人工蜂群算法,并将其应用到复杂函数优化中,实验结果表明该方法在求解速度和精度上明显优于基于遗传算法和基本人工蜂群算法的函数优化方法。
In order to optimize complex functions exactly and quickly,the basic artificial bee colony algorithm is improved by introducing adaptive competition mechanism,and is applied to complex function optimization.Experimental results indicate that the method is better than some function optimization methods based on genetic algorithm and the basic artificial bee colony algorithm in the solution speed and accuracy.
出处
《电子测试》
2013年第5S期199-200,共2页
Electronic Test
基金
海南大学应用科技学院(儋州校区)科研基金重点项目(Hyk-1204
Hyk-1213)
海南大学青年基金项目(qnjj1256)
海南省教育厅高校科研项目(Hjkj2012-11)
关键词
人工蜂群算法
遗传算法
函数优化
artificial bee colony algorithm(ABC)
Genetic algorithm(GA)
function optimization
