关键词: 乌鸦搜索算法, 共享机制, 多段扰动

Abstract: Crow search algorithm, as a new meta-heuristic intelligent algorithm, simulates the behavior of crows following each other to steal. In order to improve the convergence accuracy and late search ability of the algorithm, a new hybrid crow search algorithm is proposed based on the traditional crow search algorithm. Its core idea is to add a sharing mechanism in the algorithm, improve the position update method of random tracking in the original algorithm, reduce the blindness of search and improve the convergence speed. In different iteration stages, perturbation operations of different sizes are performed on the global optimal position, which effectively improves the probability of jumping out of the local optimal position and ensures the balance between the global search ability and the local search ability of the algorithm. Finally, through eight benchmark functions, the search performance of the five algorithms is compared and analyzed in 10, 30 and 50 dimensions. The results show that the comprehensive performance of the modified algorithm is better than other algorithms.

Key words: crow search algorithm, shared mechanism, multi-segment perturbation