Open Access
Volume 39, Number 2, April 2021
Page(s) 292 - 301
Published online 09 June 2021
  1. Shan S, Wang GG. Survey of modeling and optimization strategies to solve high-dimensional design problems with computationally-expensive black-box functions[J]. Structural and Multidisciplinary Optimization, 2010, 41(2): 219–241 [Article] [Google Scholar]
  2. Long Teng, Guo Xiaosong, Peng Lei, et al. Optimization strategy using dynamic radial basis function metamodel based on trust region[J]. Journal of Mechanical Engineering, 2014, 50(7): 184–190 [Article] (in Chinese) [Google Scholar]
  3. Ye P, Pan G, Dong Z. Ensemble of surrogate based global optimization methods using hierarchical design space reduction[J]. Structural and Multidisciplinary Optimization, 2018, 58(2): 537–554 [Article] [Google Scholar]
  4. Gu J, Li G, Dong Z. Hybrid and adaptive meta-model-based global optimization[J]. Engineering Optimization, 2012, 44(1): 87–104 [Article] [Google Scholar]
  5. Goel T, Haftka RT, Shyy W, et al. Ensemble of surrogates[J]. Structural and Multidisciplinary Optimization, 2007, 33(3): 199–216 [Article] [Google Scholar]
  6. Wang X, Wang G G, Song B, et al. A novel evolutionary sampling assisted optimization method for high-dimensional expensive problems[J]. IEEE Trans on Evolutionary Computation, 2019, 23(5): 815–827 [Article] [Google Scholar]
  7. Gu J, Li W, Shu C, et al. Hybrid meta-model based search method for expensive problems[J]. Applied Soft Computing, 2019, 77643–652 [Article] [Google Scholar]
  8. Han Z, Zhang Y, Song C X, et al.Weighted gradient-enhanced Kriging for high-dimensional surrogate modeling and design optimization[J]. AIAA Journal, 2017, 55(12): 4330–4346 [Article] [Google Scholar]
  9. Farias Fup, Antunes Are, Bastos Sma, et al. Minimization of vortex induced vibrations using surrogate based optimization[J]. Structural and Multidisciplinary Optimization, 2015, 52(4): 717–735 [Article] [Google Scholar]
  10. Long T, Wu D, Guo X, et al.Efficient adaptive response surface method using intelligent space exploration strategy[J]. Structural and Multidisciplinary Optimization, 2015, 51(6): 1335–1362 [Article] [Google Scholar]
  11. Li Chunna, Zhang Yangkang. An efficient adaptive global optimization method suitable for aerodynamic optimization[J]. Acta Aeronautica et Astronautica Sinica, 2020, 41(5): 623352[Article] (in Chinese) [Google Scholar]
  12. Ye P, Pan G. Global optimization method using adaptive and parallel ensemble of surrogates for engineering design optimization[J]. Optimization, 2017, 66(7): 1135–1155 [Article] [Google Scholar]
  13. Ye Pengcheng. Research on surrogate modeling techniques and applied to shape design of autonomous underwater glider[D]. Xi'an: Northwestern Polytechnical University, 2017 (in Chinese) [Google Scholar]
  14. Zhou Shiming, Li Daokui, Tang Guojin. Design space reduction based on the metamodeling and clustering method[J]. Chinese Journal of Computational Mechanics, 2012, 29(2): 242–248 [Article] (in Chinese) [Google Scholar]
  15. Ye Pengcheng, Pan Guang, Gao Shan. Sampling design method of fast optimal Latin hypercube[J]. Journal of Northwestern Polytechnical University, 2019, 37(4): 714–723 [Article][Article] (in Chinese) [Google Scholar]
  16. Kulfan B M. Universal parametric geometry representation method[J]. Journal of Aircraft, 2008, 45(1): 142–158 [Article] [Google Scholar]
  17. Dong H, Song B, Dong Z, et al. Multi-start space reduction (MSSR) surrogate-based global optimization method[J]. Structural and Multidisciplinary Optimization, 2016, 54(4): 907–926 [Article] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.