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Reliability Algorithm Based on Adaptive Hybrid Particle Swarm Optimization and Simulated Annealing Algorithm

The sampling center of important sampling to predict structural or mechanical reliability is often computed by gradient-based iterative programs. However, there is often no convergence when calculating the highly nonlinear limitation equation. In this paper, a hybrid particle swarm optimization (PSO) and simulated annealing (SA) stochastic optimization algorithm is proposed and applied to the important sampling. The results of numerical examples confirm the theoretical analysis and show the characteristics of global search: fast convergence and high precision. This calculative method is effective and feasible to solve the problems in reliability.