A robust optimization method based on previous optimization knowledge
ObjectivesAs solving the robust optimization (RO) problem with interval uncertainty is unduly time-consuming when the nested differential evolution algorithm is directly used, a new RO design method is proposed.MethodsIn the proposed method, individuals' response values that have been accuratel...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Editorial Office of Chinese Journal of Ship Research
2022-02-01
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| Series: | Zhongguo Jianchuan Yanjiu |
| Subjects: | |
| Online Access: | http://www.ship-research.com/cn/article/doi/10.19693/j.issn.1673-3185.02256 |
| _version_ | 1818188660690911232 |
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| author | Guochen LYU Yuansheng CHENG Jiaxiang YI Jun LIU |
| author_facet | Guochen LYU Yuansheng CHENG Jiaxiang YI Jun LIU |
| author_sort | Guochen LYU |
| collection | DOAJ |
| description | ObjectivesAs solving the robust optimization (RO) problem with interval uncertainty is unduly time-consuming when the nested differential evolution algorithm is directly used, a new RO design method is proposed.MethodsIn the proposed method, individuals' response values that have been accurately calculated within the critical distance are used to approximately predict the response values of other individuals and evaluate the robustness indexes accordingly. The accurate information of individuals' response values, which is gradually expanded in the evolutionary procedure, is also used to selectively re-evaluate the past robustness of individuals, and the critical distance is adaptively reduced on the basis of the robustness misjudgment rate.ResultsTwo numerical and one engineering examples are tested to demonstrate the applicability of the proposed algorithm. The results show that the proposed algorithm saves more than 94% of computational resources, while the estimated error is less than 2.5%.ConclusionsThe proposed method can greatly reduce the calculation time of individuals' response values in the evolution process and maintain the adaptive balance between the accuracy and cost of robustness evaluation by using previous optimization knowledge, providing a new idea and method for RO design with interval uncertainty. |
| first_indexed | 2024-12-11T23:30:28Z |
| format | Article |
| id | doaj.art-6ddc9fa67d7a412290aa47d314484e9f |
| institution | Directory Open Access Journal |
| issn | 1673-3185 |
| language | English |
| last_indexed | 2024-12-11T23:30:28Z |
| publishDate | 2022-02-01 |
| publisher | Editorial Office of Chinese Journal of Ship Research |
| record_format | Article |
| series | Zhongguo Jianchuan Yanjiu |
| spelling | doaj.art-6ddc9fa67d7a412290aa47d314484e9f2022-12-22T00:46:03ZengEditorial Office of Chinese Journal of Ship ResearchZhongguo Jianchuan Yanjiu1673-31852022-02-0117214815510.19693/j.issn.1673-3185.02256ZG2256A robust optimization method based on previous optimization knowledgeGuochen LYU0Yuansheng CHENG1Jiaxiang YI2Jun LIU3School of Naval Architecture and Ocean Engineering, Huazhong University of Science and Technology, Wuhan 430074, ChinaSchool of Naval Architecture and Ocean Engineering, Huazhong University of Science and Technology, Wuhan 430074, ChinaSchool of Naval Architecture and Ocean Engineering, Huazhong University of Science and Technology, Wuhan 430074, ChinaSchool of Naval Architecture and Ocean Engineering, Huazhong University of Science and Technology, Wuhan 430074, ChinaObjectivesAs solving the robust optimization (RO) problem with interval uncertainty is unduly time-consuming when the nested differential evolution algorithm is directly used, a new RO design method is proposed.MethodsIn the proposed method, individuals' response values that have been accurately calculated within the critical distance are used to approximately predict the response values of other individuals and evaluate the robustness indexes accordingly. The accurate information of individuals' response values, which is gradually expanded in the evolutionary procedure, is also used to selectively re-evaluate the past robustness of individuals, and the critical distance is adaptively reduced on the basis of the robustness misjudgment rate.ResultsTwo numerical and one engineering examples are tested to demonstrate the applicability of the proposed algorithm. The results show that the proposed algorithm saves more than 94% of computational resources, while the estimated error is less than 2.5%.ConclusionsThe proposed method can greatly reduce the calculation time of individuals' response values in the evolution process and maintain the adaptive balance between the accuracy and cost of robustness evaluation by using previous optimization knowledge, providing a new idea and method for RO design with interval uncertainty.http://www.ship-research.com/cn/article/doi/10.19693/j.issn.1673-3185.02256robust optimization (ro)interval uncertaintydifferential evolution (de)previous optimization knowledge |
| spellingShingle | Guochen LYU Yuansheng CHENG Jiaxiang YI Jun LIU A robust optimization method based on previous optimization knowledge Zhongguo Jianchuan Yanjiu robust optimization (ro) interval uncertainty differential evolution (de) previous optimization knowledge |
| title | A robust optimization method based on previous optimization knowledge |
| title_full | A robust optimization method based on previous optimization knowledge |
| title_fullStr | A robust optimization method based on previous optimization knowledge |
| title_full_unstemmed | A robust optimization method based on previous optimization knowledge |
| title_short | A robust optimization method based on previous optimization knowledge |
| title_sort | robust optimization method based on previous optimization knowledge |
| topic | robust optimization (ro) interval uncertainty differential evolution (de) previous optimization knowledge |
| url | http://www.ship-research.com/cn/article/doi/10.19693/j.issn.1673-3185.02256 |
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