| 融合正余弦和柯西变异的麻雀搜索算法 |
| |
| 引用本文： | 李爱莲,全凌翔,崔桂梅,解韶峰.融合正余弦和柯西变异的麻雀搜索算法[J].计算机工程与应用,2022,58(3):91-99. |
| |
| 作者姓名： | 李爱莲 全凌翔 崔桂梅 解韶峰 |
| |
| 作者单位： | 1.内蒙古科技大学 信息工程学院，内蒙古 包头 014010
2.内蒙古科技大学 基建处，内蒙古 包头 014010 |
| |
| 基金项目： | 国家自然科学基金(61763039)。 |
| |
| 摘 要： | 针对麻雀搜索算法(SSA)在寻优后期出现能力不足、种群多样性损失、易落进局部极值现象,造成SSA算法收敛速度慢、探索能力不足等问题,提出了融合正余弦和柯西变异的麻雀搜索算法(SCSSA).借助折射反向学习机制初始化种群,增加物种多样性;在发现者位置更新中引入正余弦策略以及非线性递减搜索因子和权重因子协调算法的全局和局部...
|
| 关 键 词： | 麻雀搜索算法 折射反向学习 正余弦算法 非线性递减搜索因子 柯西变异 |
Sparrow Search Algorithm Combining Sine-Cosine and Cauchy Mutation |
| |
| LI Ailian,QUAN Lingxiang,CUI Guimei,XIE Shaofeng.Sparrow Search Algorithm Combining Sine-Cosine and Cauchy Mutation[J].Computer Engineering and Applications,2022,58(3):91-99. |
| |
| Authors: | LI Ailian QUAN Lingxiang CUI Guimei XIE Shaofeng |
| |
| Affiliation: | 1.School of Information Engineering,Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia 014010, China
2.Department of Infrastructure, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia 014010, China |
| |
| Abstract: | In order to address the problems that the sparrow search algorithm（SSA） has insufficient ability, loss of population diversity ,and easy to drop into local extremes in the late stage of the search, which leads to slow convergence and insufficient exploration ability of the SSA algorithm, the sparrow search algorithm integrating sine-cosine and Cauchy mutation（SCSSA） is proposed. The refracted opposition-based learning mechanism is used to initialize the population and enhance the species diversity. The sine-cosine strategy is introduced into the discoverer position update as well as a nonlinear decreasing search factor and a weighting factor to coordinate the global and local search capability of the algorithm. To improve the ability of the SSA in acquiring the global optimal solution, the Cauchy mutation is brought into the follower position to perform disturbance update to the optimal solution. The SCSSA algorithm is evaluated by 10 classical test functions in terms of convergence speed, convergence precision, average absolute error and other indexes, and the engineering design optimization problem is introduced to validate the performance of SCSSA. The experimental results prove that the improved sparrow search algorithm significantly strengthens in the convergence speed and the seeking accuracy, and exhibits better robustness. |
| |
| Keywords: | sparrow search algorithm refracted opposition-based learning sine-cosine algorithm nonlinear decreasing search factor Cauchy mutation |
| 本文献已被 维普 万方数据 等数据库收录！ |
| 点击此处可从《计算机工程与应用》浏览原始摘要信息 |
|
点击此处可从《计算机工程与应用》下载全文 |
|
