计算机技术与发展Issue(8)：75-79,5.DOI:10.3969/j.issn.1673-629X.2015.08.016
基于单纯形的改进全局人工鱼群优化算法
Improved Global Artificial Fish Swarm Algorithm Based on Simplex Method
摘要
Abstract
In order to overcome the drawbacks of Global Artificial Fish Swarm Algorithm ( GAFSA) ,such as slow convergence and low precision optimization,a modified GAFSA ( MS GAFSA) is proposed,in which the modified simplex method is adopted to improve con-vergence precision and convergence rate. For GAFSA has a faster convergence in optimization of the early and the ability to recognize the local optimum value,a simplex is constructed based on the minimum given by GAFSA when the convergence turned to the stable point. Make the simplex move and roll by reflection,expansion and contraction. Compared the values of the simplex’ s vertexes,constructing a new simplex by the trend of function,and repeating the process till the result is accurate enough. The computational results on benchmark functions show that MS GAFSA achieves higher performance,including convergence precision and convergence rate.关键词
人工鱼群算法/全局优化/单纯形算法/数值仿真Key words
artificial fish swarm algorithm/global optimization/simplex method/numerical simulation分类
信息技术与安全科学引用本文复制引用
彭培真,俞毅,王兆嘉,蒋珉..基于单纯形的改进全局人工鱼群优化算法[J].计算机技术与发展,2015,(8):75-79,5.基金项目
国家自然科学基金资助项目(61374198) （61374198）
