Bilinear Fuzzy Genetic Algorithm and Its Application on the Optimum Design of Steel Structures with Semi-rigid Connections
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arXiv
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| Autores principales: | , |
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| Formato: | Preprint |
| Publicado: |
2024
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| _version_ | 1866913575194329088 |
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| author | Farahmand-Tabar, Salar Ashtari, Payam |
| author_facet | Farahmand-Tabar, Salar Ashtari, Payam |
| contents | An improved bilinear fuzzy genetic algorithm (BFGA) is introduced in this chapter for the design optimization of steel structures with semi-rigid connections. Semi-rigid connections provide a compromise between the stiffness of fully rigid connections and the flexibility of fully pinned connections. However, designing such structures is challenging due to the nonlinear behavior of semi-rigid connections. The BFGA is a robust optimization method that combines the strengths of fuzzy logic and genetic algorithm to handle the complexity and uncertainties of structural design problems. The BFGA, compared to standard GA, demonstrated to generate high-quality solutions in a reasonable time. The application of the BFGA is demonstrated through the optimization of steel structures with semirigid connections, considering the weight and performance criteria. The results show that the proposed BFGA is capable of finding optimal designs that satisfy all the design requirements and constraints. The proposed approach provides a promising solution for the optimization of complex structures with nonlinear behavior. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_05865 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Bilinear Fuzzy Genetic Algorithm and Its Application on the Optimum Design of Steel Structures with Semi-rigid Connections Farahmand-Tabar, Salar Ashtari, Payam Neural and Evolutionary Computing Artificial Intelligence An improved bilinear fuzzy genetic algorithm (BFGA) is introduced in this chapter for the design optimization of steel structures with semi-rigid connections. Semi-rigid connections provide a compromise between the stiffness of fully rigid connections and the flexibility of fully pinned connections. However, designing such structures is challenging due to the nonlinear behavior of semi-rigid connections. The BFGA is a robust optimization method that combines the strengths of fuzzy logic and genetic algorithm to handle the complexity and uncertainties of structural design problems. The BFGA, compared to standard GA, demonstrated to generate high-quality solutions in a reasonable time. The application of the BFGA is demonstrated through the optimization of steel structures with semirigid connections, considering the weight and performance criteria. The results show that the proposed BFGA is capable of finding optimal designs that satisfy all the design requirements and constraints. The proposed approach provides a promising solution for the optimization of complex structures with nonlinear behavior. |
| title | Bilinear Fuzzy Genetic Algorithm and Its Application on the Optimum Design of Steel Structures with Semi-rigid Connections |
| topic | Neural and Evolutionary Computing Artificial Intelligence |
| url | https://arxiv.org/abs/2411.05865 |