Kriging-Based Space Exploration Global Optimization Method in Aerodynamic Design
For complicated aerodynamic design problems, the efficient global optimization method suffered from the defect of the incorrect portrayal of the design space, resulting in bad global convergence and efficiency performance. To this end, a Kriging-based global optimization method, named the Kriging-ba...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi Limited
2023-01-01
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| Series: | International Journal of Aerospace Engineering |
| Online Access: | http://dx.doi.org/10.1155/2023/4493349 |
| _version_ | 1811165515917295616 |
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| author | Wei Zhang Zhenghong Gao Chao Wang Lu Xia |
| author_facet | Wei Zhang Zhenghong Gao Chao Wang Lu Xia |
| author_sort | Wei Zhang |
| collection | DOAJ |
| description | For complicated aerodynamic design problems, the efficient global optimization method suffered from the defect of the incorrect portrayal of the design space, resulting in bad global convergence and efficiency performance. To this end, a Kriging-based global optimization method, named the Kriging-based space exploration method (KSE), was proposed in this paper. It selected multiple promising local minima and classified them into partially and fully explored minima in terms of the fitting quality of the surrogate model. Then, the partially explored minima would be furtherly exploited. During the local search, an enhanced trust-region method was adopted to make deep exploitation. By combining local and global searches, the proposed method could improve the fitting quality of the surrogate model and the optimization efficiency. The KSE was compared to other global surrogate-based optimization methods on 12 bound-constrained testing functions with 2 to 16 design variables and 2 aerodynamic optimization problems with 24 to 77 design variables. The results indicated that the KSE generally took fewer function evaluations to find the global optima or reach the target value in most test problems, holding better efficiency and robustness. |
| first_indexed | 2024-04-10T15:38:15Z |
| format | Article |
| id | doaj.art-e3a6c50c52b349d49e284d1968a88bc7 |
| institution | Directory Open Access Journal |
| issn | 1687-5974 |
| language | English |
| last_indexed | 2024-04-10T15:38:15Z |
| publishDate | 2023-01-01 |
| publisher | Hindawi Limited |
| record_format | Article |
| series | International Journal of Aerospace Engineering |
| spelling | doaj.art-e3a6c50c52b349d49e284d1968a88bc72023-02-13T01:08:21ZengHindawi LimitedInternational Journal of Aerospace Engineering1687-59742023-01-01202310.1155/2023/4493349Kriging-Based Space Exploration Global Optimization Method in Aerodynamic DesignWei Zhang0Zhenghong Gao1Chao Wang2Lu Xia3Northwestern Polytechnical UniversityNorthwestern Polytechnical UniversityBeijing Institute of Electronic System EngineerNorthwestern Polytechnical UniversityFor complicated aerodynamic design problems, the efficient global optimization method suffered from the defect of the incorrect portrayal of the design space, resulting in bad global convergence and efficiency performance. To this end, a Kriging-based global optimization method, named the Kriging-based space exploration method (KSE), was proposed in this paper. It selected multiple promising local minima and classified them into partially and fully explored minima in terms of the fitting quality of the surrogate model. Then, the partially explored minima would be furtherly exploited. During the local search, an enhanced trust-region method was adopted to make deep exploitation. By combining local and global searches, the proposed method could improve the fitting quality of the surrogate model and the optimization efficiency. The KSE was compared to other global surrogate-based optimization methods on 12 bound-constrained testing functions with 2 to 16 design variables and 2 aerodynamic optimization problems with 24 to 77 design variables. The results indicated that the KSE generally took fewer function evaluations to find the global optima or reach the target value in most test problems, holding better efficiency and robustness.http://dx.doi.org/10.1155/2023/4493349 |
| spellingShingle | Wei Zhang Zhenghong Gao Chao Wang Lu Xia Kriging-Based Space Exploration Global Optimization Method in Aerodynamic Design International Journal of Aerospace Engineering |
| title | Kriging-Based Space Exploration Global Optimization Method in Aerodynamic Design |
| title_full | Kriging-Based Space Exploration Global Optimization Method in Aerodynamic Design |
| title_fullStr | Kriging-Based Space Exploration Global Optimization Method in Aerodynamic Design |
| title_full_unstemmed | Kriging-Based Space Exploration Global Optimization Method in Aerodynamic Design |
| title_short | Kriging-Based Space Exploration Global Optimization Method in Aerodynamic Design |
| title_sort | kriging based space exploration global optimization method in aerodynamic design |
| url | http://dx.doi.org/10.1155/2023/4493349 |
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