Evidence-Based Multidisciplinary Design Optimization with the Active Global Kriging Model
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...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2019-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2019/8390865 |
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| _version_ | 1832567202152185856 |
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| author | Fan Yang Ming Liu Lei Li Hu Ren Jianbo Wu |
| author_facet | Fan Yang Ming Liu Lei Li Hu Ren Jianbo Wu |
| author_sort | Fan Yang |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-daba54cb6c264e3ba1f261419c57dc30 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-daba54cb6c264e3ba1f261419c57dc302025-02-03T01:02:13ZengWileyComplexity1076-27871099-05262019-01-01201910.1155/2019/83908658390865Evidence-Based Multidisciplinary Design Optimization with the Active Global Kriging ModelFan Yang0Ming Liu1Lei Li2Hu Ren3Jianbo Wu4State Key Laboratory of Mechanics and Control of Mechanical Structures, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, ChinaState Key Laboratory for Strength and Vibration of Mechanical Structures, Xi’an Jiaotong University, Xi’an 710049, ChinaDepartment of Engineering Mechanics, Northwestern Polytechnincal University, Xi’an 710072, ChinaWuxi Hengding Supercomputing Center Ltd., Wuxi 214135, ChinaWuxi Hengding Supercomputing Center Ltd., Wuxi 214135, ChinaThis 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.http://dx.doi.org/10.1155/2019/8390865 |
| spellingShingle | Fan Yang Ming Liu Lei Li Hu Ren Jianbo Wu Evidence-Based Multidisciplinary Design Optimization with the Active Global Kriging Model Complexity |
| title | Evidence-Based Multidisciplinary Design Optimization with the Active Global Kriging Model |
| title_full | Evidence-Based Multidisciplinary Design Optimization with the Active Global Kriging Model |
| title_fullStr | Evidence-Based Multidisciplinary Design Optimization with the Active Global Kriging Model |
| title_full_unstemmed | Evidence-Based Multidisciplinary Design Optimization with the Active Global Kriging Model |
| title_short | Evidence-Based Multidisciplinary Design Optimization with the Active Global Kriging Model |
| title_sort | evidence based multidisciplinary design optimization with the active global kriging model |
| url | http://dx.doi.org/10.1155/2019/8390865 |
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