Vol.125, No.1, 2020, pp.383-399, doi:10.32604/cmes.2020.09588
Robust Design Optimization and Improvement by Metamodel
  • Shufang Song*, Lu Wang, Yuhua Yan
School of Aeronautics, Northwestern Polytechnical University, Xi’an, 710072, China
* Corresponding Author: Shufang Song. Email:
(This article belongs to this Special Issue: Novel Methods for Reliability Evaluation and Optimization of Complex Mechanical Structures)
Received 03 January 2020; Accepted 03 June 2020; Issue published 18 September 2020
The robust design optimization (RDO) is an effective method to improve product performance with uncertainty factors. The robust optimal solution should be not only satisfied the probabilistic constraints but also less sensitive to the variation of design variables. There are some important issues in RDO, such as how to judge robustness, deal with multi-objective problem and black-box situation. In this paper, two criteria are proposed to judge the deterministic optimal solution whether satisfies robustness requirment. The robustness measure based on maximum entropy is proposed. Weighted sum method is improved to deal with the objective function, and the basic framework of metamodel assisted robust optimization is also provided for improving the efficiency. Finally, several engineering examples are used to verify the advantages.
Robust design optimization (RDO); metamodel; maximum entropy; robustness measure; global sensitivity analysis
Cite This Article
Song, S., Wang, L., Yan, Y. (2020). Robust Design Optimization and Improvement by Metamodel. CMES-Computer Modeling in Engineering & Sciences, 125(1), 383–399.
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