基于小波精英解学习和多角度搜索的新型阴阳平衡优化算法
作者:
作者单位:

1. 上海理工大学 管理学院,上海 200093;2. 盐城工学院 信息工程学院,江苏 盐城 224051

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E-mail: 44424072@qq.com.

中图分类号:

TP301.6

基金项目:

上海市“科技创新行动计划”软科学研究重点项目(18692110500);上海市哲学社会科学规划课题(2019BGL014);上海理工大学科技发展项目(2020KJFZ040).


A novel Yin-Yang pair optimization algorithm based on wavelet elite solutions learning and multi-angle search
Author:
Affiliation:

1. School of Management,University of Shanghai for Science and Technology,Shanghai 200093,China;2. College of Information Engineering,Yancheng Institute of Technology,Yancheng 224051,China

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    摘要:

    针对基本阴阳平衡优化算法计算精度低和优化速度慢等问题,提出一种新型阴阳平衡优化算法.首先,设计小波精英解学习策略,充分利用精英解的进化信息产生高质量的解,用于算法的全局勘探和局部开发;然后,将搜索角度引入解更新方程中,以实现对算法搜索空间的全方位搜索,并对所提出算法的收敛性进行理论分析;最后,采用连续优化测试函数和瓶颈旅行商问题进行数值实验,并将所提出算法与多种智能优化方法进行比较.实验结果表明,所提出算法具有更好的优化性能.

    Abstract:

    In order to solve the problem of low calculation accuracy and slow convergence velocity of the Yin-Yang pair optimization (YYPO) algorithm, a novel YYPO (NYYPO) algorithm based on the wavelet elite solutions learning and multi-angle search is presented in this paper. Firstly, the strategy of wavelet elite solutions learning is proposed to make full use of the evolutionary information of elite solutions. High-quality solutions generated by this strategy are used in the global exploration and local exploitation of the algorithm. Then, the search angle is introduced into the solution update equation, which can realize the all-round search for the algorithm search space. The convergence of the proposed algorithm is analyzed. The continuous functions and the bottleneck traveling salesman problem are employed in the numerical experiments. The NYYPO is compared with many intelligent optimization algorithms. Experimental results demonstrate that the presented NYYPO algorithm has better optimization performance.

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引用本文

许秋艳,马良,刘勇.基于小波精英解学习和多角度搜索的新型阴阳平衡优化算法[J].控制与决策,2022,37(8):1962-1970

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  • 在线发布日期: 2022-06-29
  • 出版日期: 2022-08-20