计算机工程与应用2019，Vol.55Issue(3)：140-146,230,8.DOI:10.3778/j.issn.1002-8331.1710-0255
差分进化引导趋化算子的烟花优化算法
Fireworks Optimization Algorithm Based on Leading Differential Evolution Chemotaxis Operator
摘要
Abstract
In order to solve the default of the fireworks algorithm inter-particle exchange mechanism and the disadvan-tage that the optimal position is not solved by the objective function near the origin and the origin come up with fireworks algorithm optimization with chemotaxis operator(BFW). Using the local search advantage of the chemotaxis operator to find the best individual in every iteration to improve the whole population’s search ability. The improved algorithm has been tested on 8 benchmark functions. The experimental results show that BFW has better behaviors in convergence accuracy and speed.关键词
烟花算法/趋化因子/差分进化/函数优化/全局寻优Key words
fireworks algorithm/chemotaxis operator/differential evolution/function optimization/global optimization分类
信息技术与安全科学引用本文复制引用
刘茜,毛力,杨弘..差分进化引导趋化算子的烟花优化算法[J].计算机工程与应用,2019,55(3):140-146,230,8.基金项目
国家自然科学基金(No.71363040). （No.71363040）
