A Combined Algorithm for Solving Reliability-based Robust Design Optimization Problems

In the most of the design optimization problems, we encounter uncertainties in design variables and problem parameters. In these problems, robustness and reliability of design are so important. Both robust design and reliability-based design approaches take into consideration these aspects. However, the individual application of them doesn’t ensure the stability of product during its life cycle. In this paper, we combine both robust design and reliability-based design approaches into one model and propose a genetic and reliability analysis combined algorithm to solve this kind of problem. Moreover, to increase the efficiency of the genetic algorithm, we use the design of experiment (DOE) to find the optimal levels of the parameters of this algorithm. The application of the proposed methodology is demonstrated using a numerical example.