A Structural Reliability Analysis Approach for Uncertain Structures via a PSO-DE Hybrid Algorithm

2014 ◽  
Vol 574 ◽  
pp. 702-707
Author(s):  
Chan Hyok Jong ◽  
Guang Wei Meng ◽  
Feng Li ◽  
Li Ming Zhou ◽  
Yan Hao ◽  
...  

A structural reliability analysis approach for uncertain structures based on a PSO-DE hybrid algorithm was proposed. In order to analyze the structural non-probabilistic reliability for structures with uncertain parameters, an optimization problem by using the convex model and the penalty function method was formulated. For better convergence speed and precision, the particle swarm optimization (PSO) algorithm and the differential evolution (DE) algorithm were combined to solve the structural reliability optimization problem, this PSO-DE hybrid algorithm was based on the evolution of the cognitive experience. The numerical examples were presented to demonstrate the effectiveness and accuracy of the proposed structural reliability analysis method.

2014 ◽  
Vol 551 ◽  
pp. 679-685
Author(s):  
Chan Hyok Jong ◽  
Guang Wei Meng ◽  
Feng Li ◽  
Yan Hao ◽  
Kwan Gil Kim

This paper presents a structural non-probabilistic reliability analysis approach based on a hybrid algorithm of the simulated annealing-particle swarm optimization algorithm and the differential evolution (SAPSO-DE) algorithm. In the structural non-probabilistic reliability analysis, the problem with uncertain parameters can be formulated as an optimization problem using convex model. However, the limit state function is usually implicit for the uncertain parameters. By employing the SAPSO-DE hybrid algorithm based on the evolution of the cognitive and social experiences, the problem of the structural non-probabilistic reliability analysis is solved. A numerical example is given to illustrate the high precision and good feasibility of the present method. The results shows that this proposed approach is effective, and has the predominant capability of global optimization and convergence precision.


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