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Parallel system reliability analysis with a CECBO algorithm
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DOI：10.1007/s00158-021-02857-8.png)
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摘要
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The existing engineering structural system is featured by complicated limit state functions of high nonlinearity, resulting in the conventional reliability analysis approach that is unable to evaluate these problems accurately or even unavailable. Various analytical methods have been presented by researchers over the past decades. However, these methods have difficulties in striking a balance between accuracy and computational efficiency. This paper proposes a relatively efficient and accurate procedure to estimate the failure probability of the parallel system based on the FORM and a new metaheuristic algorithm, chaotic enhanced colliding bodies optimization algorithm (CECBO). The CECBO has shown robustness, high accuracy, and implementation simplicity for solving optimization problems from previous work. Thus, the CECBO is employed to search the point of maximum likelihood (PML), a point that yields the highest value of the probability density function in the failure domain, through solving an optimization model and then approximates the failure domain of the parallel system to estimate the failure probability accurately. The results of the test examples indicate that the proposed procedure is promising for the estimation of the failure probability of a parallel system in terms of accuracy and efficiency.
Keyword:
Enhanced colliding bodies optimization (ECBO)
Point of maximum likelihood (PML)
Chaos
System reliability
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Enhanced colliding bodies optimization for design problems with continuous and discrete variables
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