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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: email

(This article belongs to the Special Issue: Novel Methods for Reliability Evaluation and Optimization of Complex Mechanical Structures)

Computer Modeling in Engineering & Sciences 2020, 125(1), 383-399. https://doi.org/10.32604/cmes.2020.09588

Abstract

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.

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Cite This Article

APA Style
Song, S., Wang, L., Yan, Y. (2020). Robust design optimization and improvement by metamodel. Computer Modeling in Engineering & Sciences, 125(1), 383-399. https://doi.org/10.32604/cmes.2020.09588
Vancouver Style
Song S, Wang L, Yan Y. Robust design optimization and improvement by metamodel. Comput Model Eng Sci. 2020;125(1):383-399 https://doi.org/10.32604/cmes.2020.09588
IEEE Style
S. Song, L. Wang, and Y. Yan "Robust Design Optimization and Improvement by Metamodel," Comput. Model. Eng. Sci., vol. 125, no. 1, pp. 383-399. 2020. https://doi.org/10.32604/cmes.2020.09588



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