@inproceedings{7a053dff9f39423282c00979111ff518,
title = "Butterfly intelligent optimization algorithm based on Good Point Set and adaptive weight factor",
abstract = "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.",
keywords = "Adaptive weight factor, Butterfly algorithm, Dynamic switching probability, Good Point Set",
author = "Jicheng Yao and Xiaonan Luo and Fang Li and Yizhou Feng and Jundi Dou and Lixiang Dai and Songhua Xu and Ruiai Chen",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 9th International Conference on Digital Home, ICDH 2022 ; Conference date: 28-10-2022 Through 30-10-2022",
year = "2022",
doi = "10.1109/ICDH57206.2022.00037",
language = "英语",
series = "Proceedings - 2022 9th International Conference on Digital Home, ICDH 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "194--200",
editor = "Ruo-mei Wang and Zhong-xuan Luo and Bao-cai Yin and Jie-qing Tan",
booktitle = "Proceedings - 2022 9th International Conference on Digital Home, ICDH 2022",
}