重庆理工大学学报（自然科学版）2017，Vol.31Issue(2)：146-152,7.DOI:10.3969/j.issn.1674-8425(z).2017.02.024
改进的正弦余弦算法在函数优化问题中的研究
Research of Improved Sine Cosine Algorithm in Function Optimization
摘要
Abstract
The sine cosine algorithm (SCA)is a new kind of swarm intelligence algorithm which was proposed in 2015.In view of the poor local search capability and low precision of the standard sine cosine algorithm,an improved sine cosine algorithm (ISCA)was proposed.Firstly,we introduced dynamic inertia weight and balance the algorithm of local and global search ability;and the,we further strengthened the late iterative local search ability,and made parameters R1 turn from linear decreasing function into the exponential decreasing function;thirdly,we introduced self-adaptive mutation factor to enhance the diversity of the population.Finally,the improved SCA algorithm was tested on 10 classical single peak and multimodal functions,and compared it with standard SCA algorithm,particle swarm optimization (PSO)and genetic algorithm (GA).Experimental results show that the ISCA algorithm is better than other algorithms.关键词
正弦余弦算法/动态惯性权重/指数递减参数/自适应变异因子/函数优化Key words
sine cosine algorithm/dynamic inertia weight/exponential decline parameter/adaptive mutation factor/function optimization分类
信息技术与安全科学引用本文复制引用
张校非,白艳萍,郝岩,王永杰..改进的正弦余弦算法在函数优化问题中的研究[J].重庆理工大学学报（自然科学版）,2017,31(2):146-152,7.基金项目
国家自然科学基金资助项目(61275120) （61275120）
