Topology optimization (TO), which is a design optimization technique that does not require design parameters, has been attracting attention. TO has a high degree of freedom and can obtain a novel design shape suitable for desired purposes. However, the characteristics of the obtained design shape may be greatly damaged due to uncertainty such as variations in material properties. Also, when multi-objective optimization for TO is considered, an increase in the calculation load becomes a major problem. In this study, as a method for efficiently conducting multiobjective robust TO, multi-objective robust solutions can be obtained by using a single-objective robust covariance matrix adaptation evolution strategy and the hybrid method of robust genetic algorithm and multi-objective robust design optimization. The proposed method was applied to design problems of magnetic shields, and obtaining a wide range Pareto front with robustness that cannot be obtained by conventional methods is possible.

As a solution for sequence optimization, and to obtain a solution that is strong robustness to variations, a multiobjective robust design optimization (MORDO) and robust genetic algorithm (GA) are applied to a multi-objective optimization problem. As a result, it is found that the MORDO is a good method for obtaining a solution with strong robustness to condition variations, even in sequence problem optimization. Moreover, it is confirmed that the robust GA is advantageous as in regards to the calculation time. As a method for making the best use of these advantages, a hybrid method of the MORDO and robust GA is proposed and verified, and an optimum solution with the same robustness as that from the MORDO is obtained without huge loss of calculation time.