Improving Pelican Optimization Algorithm by Combining 3D Spiral Motion and Hybrid Reverse Learning Strategy
The pelican optimization algorithm(POA)has some defects,such as slow convergence speed,poor population diversi-ty,and premature.To overcome these shortcomings,an improved algorithm was propped.The improved algorithm was proposed incor-porating 3D spiral flight and a hybrid backward learning strategy.Firstly,the Gauss mapping was used to initialize the population to improve the population diversity.Secondly,the three-dimensional spiral flight and the hybrid optimal-worst backward learning strategy were used to strengthen the ability of the algorithm to jump out of the local optimum.Finally,the adaptive balance factor and adaptive step size were introduced to propose a pelican falling strategy to simulate the small changes.In the Finally,IPOA was tested by 12 benchmark functions and actual cases and compared with 8 bionic algorithms.Test results and Wilcoxon signed rank sum test results showing that IPOA has improved convergence accuracy and stability.
万方数据
维普
