Application of Particle Swarm Optimization to Structural Non-probabilistic Reliability Optimization

In order to solve the reliability optimization problem of uncertainty structures in actual engineering, an optimization model was established to minimize the structure mass with the constraints of its non-probabilistic reliability index and cross-sectional area. The non-probabilistic reliability index was derived using the convex model method for the probability set theory, and a method for structural non-probabilistic reliability optimization was proposed based on particle swarm optimization (PSO). The results of an application example show that the structure mass relative error between the uncertainty optimization method and the deterministic optimization method is barely 0.009%, when deterministic optimization parameters take average value and the expected non-probabilistic reliability index is zero. The cross-sectional area and mass of the truss structure increase with an increase in the expected non-probabilistic reliability index. When the expected non-probabilistic reliability index is 1.5, the structure mass obtained by the proposed optimization method is decreased by 0.323% compared with that by the gradient projection method.