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Optimization-Based Approaches to Uncertainty Analysis of Structures Using Non-Probabilistic Modeling:A Review

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摘要 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.
出处 《Computer Modeling in Engineering & Sciences》 2025年第4期115-152,共38页 工程与科学中的计算机建模(英文)
基金 partially supported by JSPS KAKENHI JP24K07747.
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