《计算机应用研究》|Application Research of Computers

求解高维优化问题的改进正弦余弦算法

Improved sine cosine algorithm for solving high-dimensional optimization problems

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作者 徐松金,龙文
机构 1.铜仁学院 大数据学院,贵州 铜仁 554300;2.贵州财经大学 贵州省经济系统仿真重点实验室,贵阳 550025
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文章编号 1001-3695(2018)09-2574-04
DOI 10.3969/j.issn.1001-3695.2018.09.003
摘要 提出一种改进的正弦余弦算法(简记为ISCA)。受粒子群优化(PSO)算法的启发,引入惯性权重以提高正弦余弦算法的收敛精度和加快收敛速度。此外,采取反向学习策略产生初始个体以提高种群的多样性和解的质量。采用八个高维基准测试函数进行仿真实验:在相同的最大适应度函数评价次数下,ISCA总体性能上均优于基本SCA和HGWO算法;当维数较高(D=1 000)时,ISCA所用计算量远小于HDEOO算法。实验结果表明ISCA在收敛精度和收敛速度指标上均优于对比算法。
关键词 正弦余弦算法;高维优化问题;反向学习;惯性权重
基金项目 国家自然科学基金资助项目(61463009,61364003)
贵州省科技厅、铜仁市科技局、铜仁学院联合课题(黔科合LH字[2015]7248号)
贵州省教育厅创新群体项目(黔教合KY字[2016]051)
本文URL http://www.arocmag.com/article/01-2018-09-003.html
英文标题 Improved sine cosine algorithm for solving high-dimensional optimization problems
作者英文名 Xu Songjin, Long Wen
机构英文名 1.SchoolofDataScience,TongrenUniversity,TongrenGuizhou554300,China;2.GuizhouKeyLaboratoryofEconomicsSystemSimulation,GuizhouUniversityofFinance&Economics,Guiyang550025,China
英文摘要 This paper proposed an improved sine cosine algorithm (ISCA) for solving high-dimensional function optimization problems.It inspired by particle swarm optimization (PSO) algorithm, introduced inertia weight to enhance the convergence precision and accelerate the convergence speed.In addition, in order to enhance the diversity of population and solution quality, when producing the initial individuals, it employed the opposite-based learning method.It conducted simulation experiments on the 8 benchmark high-dimensional functions.The compute consumption of ISCA was far less than HDEOO in high dimension(D=1 000), and its overall performance was much better than the basic SCA and HGWO algorithm in the same number of maximum fitness function evaluation.The experimental results demonstrate that the proposed ISCA has better performance in convergence precision and convergence speed.
英文关键词 sine cosine algorithm(SCA); high-dimensional problem; opposite-based learning(OBL); inertia weight
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收稿日期 2017/4/19
修回日期 2017/6/19
页码 2574-2577
中图分类号 TP301.6
文献标志码 A