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Evidence-Based Multidisciplinary Design Optimization with the Active Global Kriging Model

Author

Listed:
  • Fan Yang
  • Ming Liu
  • Lei Li
  • Hu Ren
  • Jianbo Wu

Abstract

This article presents an approach that combines the active global Kriging method and multidisciplinary strategy to investigate the problem of evidence-based multidisciplinary design optimization. The global Kriging model is constructed by introducing a so-called learning function and using actively selected samples in the entire optimization space. With the Kriging model, the plausibility, Pl, of failure is obtained with evidence theory. The multidisciplinary feasible and collaborative optimization strategies of multidisciplinary design optimization are combined with the evidence-based reliability analysis. Numerical examples are provided to illustrate the efficiency and accuracy of the proposed method. The numerical results show that the proposed algorithm is effective and valuable, which is valuable in engineering application.

Suggested Citation

  • Fan Yang & Ming Liu & Lei Li & Hu Ren & Jianbo Wu, 2019. "Evidence-Based Multidisciplinary Design Optimization with the Active Global Kriging Model," Complexity, Hindawi, vol. 2019, pages 1-13, November.
  • Handle: RePEc:hin:complx:8390865
    DOI: 10.1155/2019/8390865
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    References listed on IDEAS

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    1. Zhang, Z. & Jiang, C. & Wang, G.G. & Han, X., 2015. "First and second order approximate reliability analysis methods using evidence theory," Reliability Engineering and System Safety, Elsevier, vol. 137(C), pages 40-49.
    2. Feng Zhang & Shiwang Tan & Leilei Zhang & Yameng Wang & Yang Gao, 2019. "Fault Tree Interval Analysis of Complex Systems Based on Universal Grey Operation," Complexity, Hindawi, vol. 2019, pages 1-8, January.
    3. Limbourg, Philipp & de Rocquigny, Etienne, 2010. "Uncertainty analysis using evidence theory – confronting level-1 and level-2 approaches with data availability and computational constraints," Reliability Engineering and System Safety, Elsevier, vol. 95(5), pages 550-564.
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