Abstract: Product quality characteristics robust optimization design is a constraint solving problem with uncertainties. A robust optimization method based on quantified constraint satisfaction problem (QCSP) is proposed, where, the design parameter variation is expressed as the universal variable. The upper and lower bounds of the objective functions and constraint functions are calculated with the effect of the universal variable, and the robustness indicators are set according to designer’s preference. Considering the model features, a combination algorithm is applied to solve the QCSP model. Interval analysis algorithm is employed to narrow the search space of the design variables, thus valid domain box of design variables is obtained which satisfy the general optimization design constraints. The shuffled frog-leaping algorithm is used to search the Pareto optimal solutions which satisfy the robustness indices; in addition, the information entropy theory-based approach is applied to select the optimal solution. The efficiency and effectiveness of the proposed method are illustrated by the product quality characteristics robust optimization design of turbine compressor diffuser.

Key words: Domain box, Interval analysis, Product quality characteristics, Quantified constraint satisfaction problem, Robust design, Shuffled frog-leaping algorithm