首页|Multi-strategy hybrid whale optimization algorithms for complex constrained optimization problems
Multi-strategy hybrid whale optimization algorithms for complex constrained optimization problems
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
万方数据
维普
A multi-strategy hybrid whale optimization algorithm(MSHWOA)for complex constrained opti-mization problems is proposed to overcome the drawbacks of easily trapping into local optimum,slow convergence speed and low optimization precision.Firstly,the population is initialized by introducing the theory of good point set,which increases the randomness and diversity of the population and lays the foundation for the global optimization of the algorithm.Then,a novel linearly update equation of convergence factor is designed to coordinate the abilities of exploration and exploitation.At the same time,the global exploration and local exploitation capabilities are improved through the siege mecha-nism of Harris Hawks optimization algorithm.Finally,the simulation experiments are conducted on the 6 benchmark functions and Wilcoxon rank sum test to evaluate the optimization performance of the improved algorithm.The experimental results show that the proposed algorithm has more signifi-cant improvement in optimization accuracy,convergence speed and robustness than the comparison algorithm.
whale optimization algorithm(WOA)good point setnonlinear convergence fac-torsiege mechanism
WANG Zhenyu(王振宇)、WANG Lei
展开 >
School of Computer Science and Engineering,Xi'an University of Technology,Xi'an 710048,P.R.China
万方数据
维普
