Optimization-Based Approaches to Uncertainty Analysis of Structures Using Non-Probabilistic Modeling: A Review
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| Publicat a: | Computer Modeling in Engineering & Sciences vol. 143, no. 1 (2025), p. 115 |
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Tech Science Press
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| Accés en línia: | Citation/Abstract Full Text - PDF |
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| 001 | 3200121329 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 1526-1492 | ||
| 022 | |a 1526-1506 | ||
| 024 | 7 | |a 10.32604/cmes.2025.061551 |2 doi | |
| 035 | |a 3200121329 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 100 | 1 | |a Kanno, Yoshihiro | |
| 245 | 1 | |a Optimization-Based Approaches to Uncertainty Analysis of Structures Using Non-Probabilistic Modeling: A Review | |
| 260 | |b Tech Science Press |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Response analysis of structures involving non-probabilistic uncertain parameters can be closely related to optimization. This paper provides a review on optimization-based methods for uncertainty analysis, with focusing attention on specific properties of adopted numerical optimization approaches. We collect and discuss the methods based on nonlinear programming, semidefinite programming, mixed-integer programming, mathematical programming with complementarity constraints, difference-of-convex programming, optimization methods using surrogate models and machine learning techniques, and metaheuristics. As a closely related topic, we also overview the methods for assessing structural robustness using non-probabilistic uncertainty modeling. We conclude the paper by drawing several remarks through this review. | |
| 653 | |a Probability theory | ||
| 653 | |a Probabilistic models | ||
| 653 | |a Semidefinite programming | ||
| 653 | |a Mixed integer | ||
| 653 | |a Uncertainty analysis | ||
| 653 | |a Integer programming | ||
| 653 | |a Machine learning | ||
| 653 | |a Parameter uncertainty | ||
| 653 | |a Convexity | ||
| 653 | |a Mathematical programming | ||
| 653 | |a Nonlinear programming | ||
| 653 | |a Heuristic methods | ||
| 653 | |a Optimization | ||
| 653 | |a Design optimization | ||
| 653 | |a Fuzzy sets | ||
| 653 | |a Random variables | ||
| 653 | |a Design specifications | ||
| 653 | |a Algorithms | ||
| 700 | 1 | |a Takewaki, Izuru | |
| 773 | 0 | |t Computer Modeling in Engineering & Sciences |g vol. 143, no. 1 (2025), p. 115 | |
| 786 | 0 | |d ProQuest |t Advanced Technologies & Aerospace Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3200121329/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3200121329/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |