Constrained multiobjective optimization of expensive black-box functions using a heuristic branch-and-bound approach
Author:
Funder
Ministero dell’Istruzione, dell’Università e della Ricerca
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s10898-023-01336-2.pdf
Reference27 articles.
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2. Akhtar, T., Shoemaker, C.A.: Multi objective optimization of computationally expensive multi-modal functions with rbf surrogates and multi-rule selection. J. Glob. Optim. 64, 17–32 (2016)
3. Al-Dujaili, A., Suresh, S.: Dividing rectangles attack multi-objective optimization. In: 2016 IEEE Congress on Evolutionary Computation (CEC), pp. 3606–3613 (2016). https://doi.org/10.1109/CEC.2016.7744246
4. Deb, K., Thiele, L., Laumanns, M., Zitzler, E.: Scalable multi-objective optimization test problems. In: Proceedings of the 2002 Congress on Evolutionary Computation. CEC’02 (Cat. No.02TH8600), vol. 1, pp. 825–830 (2002). https://doi.org/10.1109/CEC.2002.1007032
5. Deb, K.: Multi-Objective Evolutionary Algorithms, pp. 995–1015. Springer, Berlin (2015). https://doi.org/10.1007/978-3-662-43505-2_49 . (ISBN 978-3-662-43505-2)
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