Improved Adaptive-Loop Method for Non-probabilistic Reliability-Based Design Optimization

Taking the unique superiority to handle the uncertain-but-bound problem, convex model is widely used in non-probabilistic reliability-based design optimization (NRBDO). Typically, parallel-loop method, serial-loop method and single-loop method are three basic approaches for non-deterministic design optimization. It is an essential issue to combine them together and exploit their own advantages to the full. To improve the optimization efficiency, an improved adaptive-loop method (IALM) for NRBDO is proposed in this paper. In the first phase, the reconstruction constraint function is formulated to enhance the reliability analysis with single-loop method. Due to the efficiency of single-loop method and robustness of parallel-loop method, the IALM can adaptively select a proper one based on judgment criteria. To further improve the robustness and efficiency of parallel-loop method, the enhanced chaos control (ECC) method is introduced in this paper. Numerical example is utilized to demonstrate the effectiveness of the proposed method by comparison with other existing methods in terms of numerical efficiency and stability.