Butterfly intelligent optimization algorithm based on Good Point Set and adaptive weight factor

Butterfly intelligent optimization algorithm (BOA) is an intelligent algorithm, that simulates the butterflies' smell to forage for itself and find suitable mates for mating. The existing BOA has some matters with the slow convergence speed and accuracy, and it has strong randomness of search, so this article offers a BOA based on good point set and adaptive weight factor. Firstly, the optimal point list is used to initialize species to reduce search randomness. Secondly, local search and global search capability are improved by introducing an adaptive weight factor that varies with the number of iterations. Finally, dynamic switching percent p is introduced to balance the proportion of both searches. After the data experiment, it is improved that the optimization algorithm has a better result than the original butterfly algorithm.