Abstract
The stochastic ultimate load analysis model used in the safety analysis of engineering structures can be treated as a special case of chance-constrained problems (CCP) which minimize a stochastic cost function subject to some probabilistic constraints. Some special cases (such as a deterministic cost function with probabilistic constraints or deterministic constraints with a random cost function) for ultimate load analysis have alrady been investigated by various researchers. In this paper, a general probabilistic approach to stochastic ultimate load analysis is given. In doing so, some approximation techniques are needed due to the fact that the problems at hand are too complicated to evaluate precisely. We propose two extensions of the SQP method in which the variables appear in the algorithms inexactly. These algorithms are shown to be globally convergent for all models and locally superlinearly convergent for some special cases.
Original language | English |
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Pages (from-to) | 1029-1043 |
Number of pages | 15 |
Journal | Numerical Functional Analysis and Optimization |
Volume | 17 |
Issue number | 9-10 |
DOIs | |
Publication status | Published - 1 Jan 1996 |
Externally published | Yes |
Keywords
- Chance-constrained problems
- Inexact SQP method
- Stochastic programming
- Ultimate load analysis
ASJC Scopus subject areas
- Analysis
- Signal Processing
- Computer Science Applications
- Control and Optimization