A developed surrogate-based optimization framework combining HDMR-based modeling technique and TLBO algorithm for high-dimensional engineering problems-Reference-Cited by-同舟云学术

A developed surrogate-based optimization framework combining HDMR-based modeling technique and TLBO algorithm for high-dimensional engineering problems

Published:2019-03-13 Issue:2 Volume:60 Page:663-680
ISSN:1615-147X
Container-title:Structural and Multidisciplinary Optimization
language:en
Short-container-title:Struct Multidisc Optim

Author:

Wu Xiaojing,Peng Xuhao,Chen Weisheng,Zhang Weiwei

Funder

National Natural Science Foundation of China

?111? project of China

China Postdoctoral Science Foundation

Publisher

Springer Science and Business Media LLC

Subject

Control and Optimization,Computer Graphics and Computer-Aided Design,Computer Science Applications,Control and Systems Engineering,Software

Link

http://link.springer.com/content/pdf/10.1007/s00158-019-02228-4.pdf

Reference42 articles.

1. Cai X, Qiu H, Gao L, al e (2016) An enhanced RBF-HDMR integrated with an adaptive sampling method for approximating high dimensional problems in engineering design. Struct Multidiscip Optim 53(6):1209–1229

2. Cai X, Qiu H, Gao L et al (2017) Metamodeling for high dimensional design problems by multi-fidelity simulations. Struct Multidiscip Optim 56(1):151–166

3. Chen S, Xiong Y, Chen W (2012) Multiresponse and multistage metamodeling approach for design optimization. AIAA J 47(1):206–218

4. Chung IB, Park D, Choi DH (2018) Surrogate-based global optimization using an adaptive switching infill sampling criterion for expensive black-box functions. Struct Multidiscip Optim 57:1443–1459

5. Cruz NC, Redondo JL, Álvarez JD, et.al. (2016) A parallel teaching–learning-based optimization procedure for automatic heliostat aiming. J Supercomput 1–16

Cited by 29 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Data-driven hierarchical collaborative optimization method with multi-fidelity modeling for aerodynamic optimization;Aerospace Science and Technology;2024-07

2. Evolutionary Optimization Methods for High-Dimensional Expensive Problems: A Survey;IEEE/CAA Journal of Automatica Sinica;2024-05

3. A review of surrogate-assisted design optimization for improving urban wind environment;Building and Environment;2024-04

4. Teaching learning based optimization-a review on background and development;AIP Conference Proceedings;2024

5. Engineering optimization;Decision-Making Models;2024