信息与控制2016，Vol.45Issue(3)：361-370,10.DOI:10.13976/j.cnki.xk.2016.0361
求解多模态函数优化的微果蝇优化算法
Micro Fly Optimization Algorithm Solving Multi-modal Function Optimization
摘要
Abstract
To solve the problem of higher-dimensional multi-modal function optimization,this work investigates a micro-population fly optimization algorithm.In the algorithm design,a local mutation strategy ensures the elitist sub-population to achieve strong exploitation,whereas the elitist individual identified in the process of evolution guides individuals included in the medium sub-population to transform towards specific directions.Moreover,the elitist and worst individuals help the inferior sub-population seek diverse and high-quality individuals along multiple directions.One such algorithm has the merits of structural simplicity,few parameters,strong evolution,and so on.Comparative numerical results show that the algorithm with strong global optimization and high efficiency has great potential for solving higher-dimensional function optimization problems.关键词
果蝇优化/小种群/多模态函数优化/偏高维Key words
fly optimization/micro population/multi-modal function optimization/higher dimensionality分类
信息技术与安全科学引用本文复制引用
张晓茹,张著洪..求解多模态函数优化的微果蝇优化算法[J].信息与控制,2016,45(3):361-370,10.基金项目
国家自然科学基金资助项目(61563009) （61563009）
教育部博士点基金资助项目(20125201110003) （20125201110003）
贵州大学研究生创新基金资助项目(研理工2015057) （研理工2015057）
