Kriging-Based Performance Measure Function Approximation Method for Hybrid Reliability-Based Design Optimization

Hybrid reliability-based design optimization (HRBDO) can provide an effective way to obtain the optimum in presence of both random and interval variables. HRBDO is typically described as a nested model. It computationally expensive when directly solving problem by method. To address this issue, paper develops efficient decoupled method that aims at performance measure function approximation adaptive Kriging model (KPMFA). The proposed KPMFA includes three main blocks, namely hybrid inverse reliability analysis, approximation, equivalent deterministic optimization. In KPMFA, adaptation chaos control (ACC) algorithm for analysis accommodates variables developed. Moreover, strategy with two-stage enrichment developed approximate functions on region interest. Then, be proceeded using functions. Finally, five illustrative problems are investigated demonstrate accuracy efficiency