1. 基于自适应调整权重和搜索策略的鲸鱼优化算法.
- Author
-
孔 芝, 杨青峰, 赵 杰, and 熊浚钧
- Subjects
- *
MATHEMATICAL optimization , *CURRENT distribution , *GLOBAL optimization , *WHALES , *PARTICLE swarm optimization , *PROBLEM solving - Abstract
The whale optimization algorithm(WOA) has slow convergence speed and low convergence accuracy and tends to fall into local optimum.In order to solve these problems， a whale optimization algorithm(AWOA) based on adaptive adjustment of weight and search strategy was proposed.An adaptive adjustment of weight with the current distribution of whale population was designed to improve the convergence speed of the algorithm， and an adaptive adjustment of search strategy was designed to improve the ability of the algorithm to jump out of local optimum.Using 23 standard test functions， the algorithm was tested for high-dimensional and low-dimensional problems， respectively.The simulation results showed that the AWOA is generally superior to other improved whale optimization algorithms in terms of convergence accuracy and convergence speed. [ABSTRACT FROM AUTHOR]
- Published
- 2020
- Full Text
- View/download PDF