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Solving advanced multi-objective robust designs by means of multiple objective evolutionary algorithms (MOEA): A reliability application

机译：通过多目标进化算法（MOEA）解决高级多目标鲁棒设计：可靠性应用

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This paper extends the approach proposed by the second author in [Rocco et al. Robust design using a hybrid-cellular-evolutionary and interval-arithmetic approach: a reliability application. In: Tarantola S, Saltelli A, editors. SAMO 2001: Methodological advances and useful applications of sensitivity analysis. Reliab Eng Syst Saf 2003;79(2):149-59 [special issue]] to obtain a robust system design. The approach based on the use of evolutionary algorithms and interval arithmetic finds the maximum-volume inner box (MIB) or the maximal ranges of variation for each variable that preserve pre-specified design/performance requirements. The original single-objective formulation considers the definition of a MIB around a specified centroid (case 1), or around an unspecified centroid (case 2). In this paper, both cases were successfully modified and solved as multiple-objective (MO) problems, showing the advantages of MO formulations in a design-selection decision framework. Special attention is devoted to the unspecified centre MO problem where the computational efficiency could be a critical issue. In that sense, a new procedure based on the "percentage representation" is proposed. This approach reduces drastically the computational burden, extending the possibilities of use of robust design.
机译：本文扩展了第二作者在[Rocco et al。使用混合细胞进化和区间算术方法的稳健设计：可靠性应用。在：塔兰托拉S，萨尔特利A，编辑。 SAMO 2001：灵敏度分析的方法学进展和有用应用。 Reliab Eng Syst Saf 2003; 79（2）：149-59 [特刊]]以获取可靠的系统设计。该方法基于进化算法和区间算法的使用，找到了保留预先指定的设计/性能要求的每个变量的最大容积内箱（MIB）或最大变化范围。原始的单目标公式考虑了围绕指定质心（情况1）或围绕未指定质心（情况2）的MIB定义。在本文中，这两种情况都被成功修改并解决为多目标（MO）问题，显示了MO公式在设计选择决策框架中的优势。特别关注未指定的中心MO问题，其中计算效率可能是一个关键问题。从这个意义上讲，提出了一种基于“百分比表示”的新程序。这种方法大大减少了计算负担，扩展了使用健壮设计的可能性。

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