A fast interpolation-based multi-objective evolutionary algorithm for large-scale multi-objective optimization problems
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Geometry and Topology,Theoretical Computer Science,Software
Link
https://link.springer.com/content/pdf/10.1007/s00500-023-09468-z.pdf
Reference58 articles.
1. Agarwal D, Singh P, Sayed MAE (2023) The Karush–Kuhn–Tucker (KKT) optimality conditions for fuzzy-valued fractional optimization problems. Math Comput Simul 205:861–877. https://doi.org/10.1016/j.matcom.2022.10.024
2. Antonio LM, Coello CAC (2013) Use of cooperative coevolution for solving large scale multiobjective optimization problems. In: Proceedings of IEEE congress evolutionary computation (CEC), Cancun, Mexico. pp 2758–2765. https://doi.org/10.1109/CEC.2013.6557903
3. Antonio LM, Coello CAC (2016) Indicator-based cooperative coevolution for multi-objective optimization. In: Proceedings of IEEE congress evolutionary computation (CEC), Vancouver, BC, Canada. pp 991–998 . https://doi.org/10.1109/CEC.2016.7743897
4. Antonio LM, Coello CAC, Morales MAR, Brambila SG, González JF, Tapia GC (2020) Coevolutionary operations for large scale multi-objective optimization. In: Proceedings of IEEE congress evolutionary computation (CEC). pp 1–8. https://doi.org/10.1109/CEC48606.2020.9185846
5. Bader J, Zitzler E (2011) HypE: an algorithm for fast hypervolume-based many-objective optimization. Evol Comput 19(1):45–76
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