中北大学学报（自然科学版）2016，Vol.37Issue(6)：570-575,6.DOI:10.3969/j.issn.1673-3193.2016.06.004
基于自适应步长的果蝇优化算法
Fruit Fly Optimization Algorithm Based on Adaptive Step Size
摘要
Abstract
Considering the premature convergence problems of slow optimizing speed,low convergence precision and easy local extremum for standard fruit fly optimization algorithm(SFOA)with the fixed-length step,a new FOA based on adaptive step size,named FOABASS,was presented by analyzing the relation of step size and searching ability of fruit fly.In FOABASS,the step size in search was created on the condition of dynamic step size which varies with current swarm location and evolution generation. Then,the high capacity of new algorithm for finding the global optimum and the balance between global exploration and local exploitation ability was obtained.Finally,simulation results of FOABASS,SFOA algorithm and other modified version show the superiority and the effectiveness of FOABASS.关键词
果蝇优化算法/函数优化/自适应步长/局部极值Key words
fruit fly optimization algorithm/function optimization/adaptive step size/local extremum分类
信息技术与安全科学引用本文复制引用
郭晓东,王丽芳,张学良..基于自适应步长的果蝇优化算法[J].中北大学学报（自然科学版）,2016,37(6):570-575,6.基金项目
太原科技大学博士科研启动基金资助项目(20122009) （20122009）
山西省优秀研究生创新项目(20113121) （20113121）
国家自然科学基金青年项目(61003053) （61003053）
