Robust optimization is a method for optimization under uncertainties in engineering systems and designs for applications ranging from aeronautics to nuclear. In a robust design process, parameter variability (or uncertainty) is incorporated into the engineering systems' optimization process to assure the systems' quality and reliability. This chapter focuses on a robust optimization approach for developing robust and reliable advanced systems and explains the framework for using uncertainty quantification and optimization techniques. For the uncertainty analysis, a polynomial chaos-based approach is combined with the optimization algorithms MOSA (Multi-Objective Simulated Annealing), and the process is discussed with a simplified test function. For the optimization process, gradient-free genetic algorithms are considered as the optimizer scans the whole design space, and the optimal values are not always dependent on the initial values.

翻译：强力优化是一种在工程系统和从航空到核应用的设计的不确定性下优化的方法。在一个稳健的设计过程中,参数变异(或不确定性)被纳入工程系统的优化过程,以确保系统的质量和可靠性。本章侧重于开发稳健可靠的先进系统的稳健优化方法,并解释了使用不确定性量化和优化技术的框架。在不确定性分析中,基于多元混乱的方法与优化算法MOSA(多目标模拟安纳林)相结合,该过程与简化的测试功能讨论。对于优化过程,将无梯度遗传算法视为优化者扫描整个设计空间,而最佳值并不总是取决于初始值。