精英反向黄金正弦被囊群优化算法

Elite Opposition-based Golden-Sine Tunicate Swarm Algorithm

针对被囊群算法(Tunicate Swarm Algorithm,TSA)存在的收敛精度低,寻优性能不足等问题,结合精英反向学习策略与黄金正弦算法,提出了精英反向黄金正弦被囊群算法(Elite Opposition-based Golden-Sine Tunicate Swarm Algorithm,EGolden-STSA)。该算法通过提高种群多样性及其质量,提升了算法收敛速度与寻优精度。通过对10个基本测试函数进行寻优实验,且与单一策略改进算法进行对比,结果显示出精英反向黄金正弦被囊群优化算法具有更好的寻优能力,验证了优化方法的有效性。将改进的算法进一步用于求解高维问题,实验结果同样显示了其具有良好的寻优性能,算法改进效果明显。

In order to solve the problems of low convergence accuracy and insufficient optimization performance of the Tunicate Swarm Algorithm,Elite opposition-based Golden-Sine Tunicate Swarm Algorithm is proposed.By improving the diversity and quality of the population,the algorithm improves the convergence speed and optimization accuracy of the algorithm.Through the optimization experiments of 10 basic test functions,and compared with the single strategy improved algorithm,the results show that the Elite opposition-based Golden-Sine Tunicate Swarm Algorithm has better optimization ability,which verifies the effectiveness of the optimization method.The improved algorithm is further applied to solve high-dimensional problems,and the experimental results also show that it has good optimization performance,and the improvement effect of the algorithm is obvious.