Reliability analysis is an important and practical way of considering uncertainty in an engineering system. In practical engineering, the limit state functions are usually implicit in terms of random variables. Traditional reliability analysis methods are time‐consuming and require derivative computing. In this paper, particle swarm optimization (PSO) is applied to reliability analysis by combining it with the first‐order reliability method. To improve the global search performance, chaotic PSO (CPSO) was proposed by combining PSO with a chaotic system. CPSO‐based reliability analysis is described and applied to four classic examples. The results show that implementation of CPSO‐based reliability analysis is easy and can yield a reliability index and design point with good accuracy. The proposed method was applied to analyze the reliability of a circular tunnel in different cases. The results show that the CPSO algorithm is very efficient at solving global optimization problems and is a good approach for reliability analysis. Copyright © 2014 John Wiley & Sons, Ltd.
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