A decoupled credibility-based design optimization method for fuzzy design variables by failure credibility surrogate modeling
| Autor: | Lu Wang, Beixi Jia, Zhenzhou Lu |
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| Rok vydání: | 2020 |
| Předmět: |
Mathematical optimization
Control and Optimization Small data Optimization algorithm Computer science Computation Constraint (computer-aided design) 0211 other engineering and technologies 02 engineering and technology Computer Graphics and Computer-Aided Design Fuzzy logic Fuzzy uncertainty Computer Science Applications 020303 mechanical engineering & transports 0203 mechanical engineering Control and Systems Engineering Credibility Engineering design process Software 021106 design practice & management |
| Zdroj: | Structural and Multidisciplinary Optimization. 62:285-297 |
| ISSN: | 1615-1488 1615-147X |
| DOI: | 10.1007/s00158-020-02487-6 |
| Popis: | In order to make a good compromise of cost and safety with small data in the early structural design stage, a practical decoupled credibility-based design optimization method is developed in the presence of fuzzy uncertainty. In the proposed approach, failure credibility is constructed as optimization constraints estimated by fuzzy advanced first-order second-moment method. By approximating the fuzzy credibility constraint by the adaptive Kriging surrogate model, a fuzzy credibility-based design is decoupled to a common deterministic optimization so that various existing optimization algorithms can be easily applied. Compared to the traditional double-loop approach, the newly proposed method is more efficient and strongly practical for complicated engineering problems. Design results of three structural engineering examples also show advantages in accuracy and computation speed of the proposed method over the traditional double-loop approach. |
| Databáze: | OpenAIRE |
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