Reliability-based robust multi-objective optimization applied to engineering system design

• Published in: Engineering optimization Vol. 52; no. 1; pp. 1 - 21
• Main Authors: Lobato, Fran Sérgio, da Silva, Márcio Aurelio, Cavalini Jr, Aldemir Ap, Steffen Jr, Valder
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis 02.01.2020; Taylor & Francis Ltd
• Subjects: Design optimization; differential evolution; engineering systems; Evolutionary algorithms; Evolutionary computation; Methodology; multi-objective optimization; Multiple objective analysis; Probabilistic methods; Probability theory; Reliability analysis; Reliability engineering; Reliability-based design; Robust design; Robustness; Rotor dynamics; Systems design
• ISSN: 0305-215X; 1029-0273
• DOI: 10.1080/0305215X.2019.1577413

Probabilistic and non-probabilistic methods have been proposed to deal with design problems under uncertainties. Reliability-based design and robust design are probabilistic strategies traditionally used for this purpose. In the present contribution, reliability-based robust design optimization (RBRDO) is formulated as a multi-objective problem considering the interaction of both approaches. The proposed methodology is based on the differential evolution algorithm associated with two strategies to deal with reliability and robustness, respectively, namely inverse reliability analysis and the effective mean concept. This multi-objective optimization problem considers the maximization of reliability and robustness coefficients as additional objective functions. The effectiveness of the methodology is illustrated by two classical test cases and a rotor-dynamics application. The results demonstrate that the proposed methodology is an alternative method to solve RBRDO problems.