A multi-objective robust optimization approach for engineering design under interval uncertainty
Abstract
Purpose
Engineering system design and optimization problems are usually multi-objective and constrained and have uncertainties in the inputs. These uncertainties might significantly degrade the overall performance of engineering systems and change the feasibility of the obtained solutions. This paper aims to propose a multi-objective robust optimization approach based on Kriging metamodel (K-MORO) to obtain the robust Pareto set under the interval uncertainty.
Design/methodology/approach
In K-MORO, the nested optimization structure is reduced into a single loop optimization structure to ease the computational burden. Considering the interpolation uncertainty from the Kriging metamodel may affect the robustness of the Pareto optima, an objective switching and sequential updating strategy is introduced in K-MORO to determine (1) whether the robust analysis or the Kriging metamodel should be used to evaluate the robustness of design alternatives, and (2) which design alternatives are selected to improve the prediction accuracy of the Kriging metamodel during the robust optimization process.
Findings
Five numerical and engineering cases are used to demonstrate the applicability of the proposed approach. The results illustrate that K-MORO is able to obtain robust Pareto frontier, while significantly reducing computational cost.
Practical implications
The proposed approach exhibits great capability for practical engineering design optimization problems that are multi-objective and constrained and have uncertainties.
Originality/value
A K-MORO approach is proposed, which can obtain the robust Pareto set under the interval uncertainty and ease the computational burden of the robust optimization process.
Keywords
Acknowledgements
This research has been supported by the National Natural Science Foundation of China (NSFC) under Grant No. 51505163, No. 51323009 and No. 51421062, National Basic Research Program (973 Program) of China under Grant No. 2014CB046703 and the Fundamental Research Funds for the Central Universities, HUST under Grant No. 2016YXMS272. The authors also would like to thank the anonymous referees for their valuable comments.
Citation
Zhou, Q., Shao, X., Jiang, P., Xie, T., Hu, J., Shu, L., Cao, L. and Gao, Z. (2018), "A multi-objective robust optimization approach for engineering design under interval uncertainty", Engineering Computations, Vol. 35 No. 2, pp. 580-603. https://doi.org/10.1108/EC-09-2016-0320
Publisher
:Emerald Publishing Limited
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