Fuzzy clustering of structural members for efficient design optimization
Author:
Publisher
Springer Science and Business Media LLC
Subject
Civil and Structural Engineering
Link
https://link.springer.com/content/pdf/10.1007/s42107-022-00525-w.pdf
Reference35 articles.
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2. Angelo Jaqueline, S., Bernardino, H. S., & Barbosa, H. J. C. (2015). Ant colony approaches for multiobjective structural optimization problems with a cardinality constraint. Advances in Engineering Software, 80, 101–115. https://doi.org/10.1016/j.advengsoft.2014.09.015
3. Assanai, T., & Cheerarot, R. (2017). Optimal parameters and performance of artificial bee colony algorithm for minimum cost design of reinforced concrete frames. Engineering Structures, 151, 802–820. https://doi.org/10.1016/j.engstruct.2017.08.059
4. Barbosa Helio, J.C., & Afonso C.C. L. (2005) A genetic algorithm encoding for a class of cardinality constraints. In Genetic and Evolutionary Computation Conference, GECCO 05. https://doi.org/10.1145/1068009.1068206
5. Barbosa Helio, J. C., Lemonge, A. C. C., & Borges, C. C. H. (2008). A genetic algorithm encoding for cardinality constraints and automatic variable linking in structural optimization. Engineering Structures, 30(12), 3708–3723. https://doi.org/10.1016/j.engstruct.2008.06.014
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