A knowledge-driven monarch butterfly optimization algorithm with self-learning mechanism
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence
Link
https://link.springer.com/content/pdf/10.1007/s10489-022-03999-y.pdf
Reference49 articles.
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3. Zhao F, He X, Wang L (2021) A two-stage cooperative evolutionary algorithm with problem-specific knowledge for energy-efficient scheduling of no-wait flow-shop problem. IEEE Trans Cybern 51:5291–5303. https://doi.org/10.1109/TCYB.2020.3025662
4. Zhao F, Liu Y, Shao Z et al (2015) A chaotic local search based bacterial foraging algorithm and its application to a permutation flow-shop scheduling problem. 29:962–981. https://doi.org/10.1080/0951192X.2015.1130240
5. Wang F, Zhang H, Li K, Lin Z, Yang J, Shen XL (2018) A hybrid particle swarm optimization algorithm using adaptive learning strategy. Inf Sci (Ny) 436–437:162–177. https://doi.org/10.1016/j.ins.2018.01.027
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