采用多模式飞行的乌鸦搜索算法.

Aiming at the shortcomings of crow search algorithm ( CSA), this paper proposed a crow search algorithm using multi-mode flight ( MFCSA) . Based on the strength of foraging ability, the algorithm divided the population into two groups: strong and weak foraging ability. Those with strong foraging ability adopted the strategy of trailing and tracking the optimal target of the current group, and flied to the vicinity of the current optimal position of the group under the guidance of the group information to carry out search activities, which enhanced the local exploitation ability of the algorithm. Those with weaker foraging ability adopted the two strategies of observing and learning the foraging methods of the strong, and flying away quickly when encountering danger, the former could improve the global exploration ability of the algorithm, and the latter could maintain the diversity of the population. Through the numerical experiment simulation of 15 benchmark test functions and 2 engineering application problems, the results show that the MFCSA has better performance in optimization accuracy, convergence speed, etc., enhances the ability to avoid falling into the local optimum, and has better stability. [ABSTRACT FROM AUTHOR]