基于螺旋搜索机制的行星搜索算法

螺旋搜索机制的全局搜索能力强，广泛用于萤火虫算法及鲸鱼搜索算法，但其收敛速度慢，收敛精度低，局部搜索能力较差。通过改变收敛范围较小时的搜索模式，提出了局部螺旋搜索来提高其局部搜索能力，并引入变异操作提高其局部搜索能力，提出了行星搜索算法。通过对单峰及多峰值测试函数对该算法进行验证。结果表明行星搜索算法在收敛速度、搜索精度及局部搜索能力等方面较粒子群算法、萤火虫算法及鲸鱼搜索算法等有明显提升。

Planet search algorithm based on spiral search mechanism

Spiral search mechanism has strong global search ability and is widely used in firefly and whale search algorithms, but its convergence speed is slow, the convergence accuracy is low, and the local search ability is poor. By changing the search mode with small convergence range, a local spiral search is proposed to improve its local search ability, and a mutation operation is introduced to improve its local search ability, and a planet search algorithm is proposed. The algorithm is verified by single - peak and multi - peak test functions. The results show that the planet search algorithm is better than particle swarm optimization, firefly algorithm and whale search algorithm in convergence speed, search accuracy and local search ability.