Optimization-Based Approaches to Uncertainty Analysis of Structures Using Non-Probabilistic Modeling: A Review
محفوظ في:
| الحاوية / القاعدة: | Computer Modeling in Engineering & Sciences vol. 143, no. 1 (2025), p. 115 |
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| المؤلف الرئيسي: | |
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| منشور في: |
Tech Science Press
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| الموضوعات: | |
| الوصول للمادة أونلاين: | Citation/Abstract Full Text - PDF |
| الوسوم: |
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| مستخلص: | 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. |
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| تدمد: | 1526-1492 1526-1506 |
| DOI: | 10.32604/cmes.2025.061551 |
| المصدر: | Advanced Technologies & Aerospace Database |