计算机技术与发展2017，Vol.27Issue(11)：41-45,5.DOI:10.3969/j.issn.1673-629X.2017.11.009
自适应修改权重参数的果蝇优化算法
A Fruit Fly Optimization Algorithm with Adaptive Modifying Weight Parameters
摘要
Abstract
In view of the defects of easily falling into local extreme,slow convergence speed in later iteration and low convergence preci-sion for fruit fly optimization algorithm,a fruit fly optimization algorithm based on adaptive modifying weight parameters is proposed considering individual cognitive factor and group guiding factor of particle swarm optimization. It introduces individual cognitive factor and group guiding factor so that the individual has sufficient awareness on its own position and the group has a good guide on the individ-uals. In each loop of iteration it dynamically has modified size of cognitive factor and guiding factor based on the current value of fitness of the fruit fly group and regulated iterative step size by adaptive method,which makes it avoid the premature convergence and improve its convergence accuracy and convergence rate. Experimental results of standard test functions show that it can jump out of local extreme with advantages of more precise and faster convergence.关键词
果蝇优化算法/自适应/迭代步长/认知因子/引导因子Key words
fruit fly optimization algorithm/adaptive/iterative step/cognitive factor/guiding factor分类
信息技术与安全科学引用本文复制引用
牛勇力,吴清,李平娜,谢章华..自适应修改权重参数的果蝇优化算法[J].计算机技术与发展,2017,27(11):41-45,5.基金项目
国家自然科学基金资助项目(21276063,21476059) （21276063,21476059）
河北省科技支撑项目(16273101D) （16273101D）
