1. 混合策略改进的鲸鱼优化算法.
- Author
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郝晓弘, 宋吉祥, 周 强, and 马 明
- Subjects
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MATHEMATICAL optimization , *ALGORITHMS , *SEARCH algorithms , *WHALES , *PARTICLE swarm optimization , *PROBLEM solving - Abstract
In order to solve the problems of slow search speed, premature convergence and low search accuracy of standard whale optimization algorithm, this paper proposed a hybrid strategy to improve whale optimization algorithm. Firstly, it increased the population diversity by generating the initial population with chaotic map, which laid a foundation for the algorithm global search. Then, by the non-linear strategy, it improved the convergence factor and inertia weight to balance the global exploration, local development ability of the algorithm and accelerated the convergence speed. Finally, according to the variance of the group fitness, it set the threshold performing the mutation operation to avoid the premature convergence of the algorithm. By testing 12 typical benchmark functions in three aspects, the experimental results show that the improved algorithm has a remarkable enhancement in search speed and convergence accuracy. Besides, it has a strong ability to get rid of falling into local optimum. [ABSTRACT FROM AUTHOR]
- Published
- 2020
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