Wang Fang, Wang Peng, Jiao Yuwei
Chengdu Institute of Computer Application, Chinese Academy of Sciences, Chengdu 610213, China.
School of Computer Science and Engineering, Southwest Minzu University, Chengdu 610041, China.
Entropy (Basel). 2024 Aug 23;26(9):719. doi: 10.3390/e26090719.
The method of quantum dynamics is employed to investigate the mean strategy in the swarm intelligence algorithm. The physical significance of the population mean point is explained as the location where the optimal solution with the highest likelihood can be found once a quantum system has reached a ground state. Through the use of the double well function and the CEC2013 test suite, controlled experiments are conducted to perform a comprehensive performance analysis of the mean strategy. The empirical results indicate that implementing the mean strategy not only enhances solution diversity but also yields accurate, efficient, stable, and effective outcomes for finding the optimal solution.
采用量子动力学方法研究群体智能算法中的均值策略。群体均值点的物理意义被解释为量子系统达到基态后最有可能找到最优解的位置。通过使用双阱函数和CEC2013测试套件，进行了对照实验以对均值策略进行全面的性能分析。实证结果表明，实施均值策略不仅提高了解的多样性，而且在寻找最优解方面产生了准确、高效、稳定且有效的结果。
