A modified teaching learning metaheuristic algorithm with opposite-based learning for permutation flow-shop scheduling problem
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Cognitive Neuroscience,Computer Vision and Pattern Recognition,Mathematics (miscellaneous)
Link
https://link.springer.com/content/pdf/10.1007/s12065-020-00487-5.pdf
Reference82 articles.
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3. Du W, Tang Y, Leung SYS, Tong L, Vasilakos AV, Qian F (2018) Robust order scheduling in the discrete manufacturing industry: a multiobjective optimization approach. IEEE Trans Ind Inf 14(1):253–264. https://doi.org/10.1109/TII.2017.2664080
4. Hidri L, Gharbi A (2017) New efficient lower bound for the hybrid flow shop scheduling problem with multiprocessor tasks. IEEE Access 5:6121–6133. https://doi.org/10.1109/ACCESS.2017.2696118
5. Bargaoui H, Driss OB, Ghédira K (2017) Towards a distributed implementation of chemical reaction optimization for the multi-factory permutation flowshop scheduling problem. Procedia Comput Sci 112:1531–1541. https://doi.org/10.1016/j.procs.2017.08.057
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