摘要
针对标准正余弦算法进化后期的停滞问题,对进化过程中的种群多样性进行分析,得出标准正余弦算法的种群多样性受控制因子的直接影响,且种群多样性表达式中控制因子指数随迭代次数的增加而下降.为了改善标准正余弦算法进化后期的探索和开采,提出多尺度正余弦优化算法.该算法通过自适应的多尺度控制因子调节群体多样性从而实现多层次的搜索;同时设计协助种群实施局部搜索,其种群独立进化,个体可以直接学习主群或协助种群中的最优个体,以加快收敛速度和提高解的质量.将所提出算法与改进的正余弦算法和新型群智能算法进行对比实验,实验结果表明,所提出算法能够较好地平衡进化过程中的探索和开采,提高全局优化能力.
In order to address the stagnation problem in the late stage of evolution of the standard sine cosine algorithm(SCA),this paper makes the analysis of population diversity.The analysis results show that the control factor affects directly population diversity and is decreased exponentially with increase of iterations in the expression of population diversity.In order to improve the ability of exploration and exploitation in the late stage of evolution of the SCA,a multi-scale sine cosine algorithm(MSCA)is presented.In the MSCA,an adaptive multi-scale control factor is designed to regulate population diversity for achieving the search with different layers.Meanwhile,an assisted swarm is developed to coordinate the local search for accelerating the convergence speed and improving calculation accuracy.The assisted swarm evolves independently and each individual can learn from the best experience of the mast swarm or the assisted swarm.The MSCA is evaluated on 23 benchmark functions and compared with the improved versions of the SCA and new swarm intelligence algorithms.The numerical results show that the MSCA can better coordinate the exploitation and exploration capabilities and improve the global optimization ability.
作者
申元霞
张学锋
方馨
汪小燕
SHEN Yuan-xia;ZHANG Xue-feng;FANG Xin;WANG Xiao-yan(School of Computer Science and Technology,Anhui University of Technology,Ma’anshan 243000,China)
出处
《控制与决策》
EI
CSCD
北大核心
2022年第11期2860-2868,共9页
Control and Decision
基金
安徽高校自然科学研究项目(KJ2019A0063)
安徽省自然科学基金项目(1808085MF196)。
关键词
正余弦算法
停滞问题
种群多样性
探索和开采
控制因子
全局优化
SCA
stagnation problem
population diversity
exploration and exploitation
control factor
global optimization
