Optimization of high-dimensional expensive multi-objective problems using multi-mode radial basis functions
Abstract Numerous surrogate-assisted evolutionary algorithms are developed for multi-objective expensive problems with low dimensions, but scarce works have paid attention to that with high dimensions, i.e., generally more than 30 decision variables. In this paper, we propose a multi-mode radial bas...
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| Format: | Article |
| Language: | English |
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Springer
2025-01-01
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| Series: | Complex & Intelligent Systems |
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| Online Access: | https://doi.org/10.1007/s40747-024-01737-0 |
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| author | Jiangtao Shen Xinjing Wang Ruixuan He Ye Tian Wenxin Wang Peng Wang Zhiwen Wen |
| author_facet | Jiangtao Shen Xinjing Wang Ruixuan He Ye Tian Wenxin Wang Peng Wang Zhiwen Wen |
| author_sort | Jiangtao Shen |
| collection | DOAJ |
| description | Abstract Numerous surrogate-assisted evolutionary algorithms are developed for multi-objective expensive problems with low dimensions, but scarce works have paid attention to that with high dimensions, i.e., generally more than 30 decision variables. In this paper, we propose a multi-mode radial basis functions-assisted evolutionary algorithm (MMRAEA) for solving high-dimensional expensive multi-objective optimization problems. To improve the reliability, the proposed algorithm uses radial basis functions based on three modes to cooperate to provide the qualities and uncertainty information of candidate solutions. Meanwhile, bi-population based on competitive swarm optimizer and genetic algorithm are applied for better exploration and exploitation in high-dimensional search space. Accordingly, an infill criterion based on multi-mode of radial basis functions that comprehensively considers the quality and uncertainty of candidate solutions is proposed. Experimental results on widely-used benchmark problems with up to 100 decision variables demonstrate the effectiveness of our proposal. Furthermore, the proposed method is applied to the structure optimization of the blended-wing-body underwater glider (BWBUG) and gets impressive solutions. |
| format | Article |
| id | doaj-art-76c4d0325164485db752434050e57585 |
| institution | Kabale University |
| issn | 2199-4536 2198-6053 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Springer |
| record_format | Article |
| series | Complex & Intelligent Systems |
| spelling | doaj-art-76c4d0325164485db752434050e575852025-02-09T13:01:14ZengSpringerComplex & Intelligent Systems2199-45362198-60532025-01-0111212210.1007/s40747-024-01737-0Optimization of high-dimensional expensive multi-objective problems using multi-mode radial basis functionsJiangtao Shen0Xinjing Wang1Ruixuan He2Ye Tian3Wenxin Wang4Peng Wang5Zhiwen Wen6School of Marine Science and Technology, Northwestern Polytechnical UniversitySchool of Marine Science and Technology, Northwestern Polytechnical UniversitySchool of Marine Science and Technology, Northwestern Polytechnical UniversityKey Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, Institutes of Physical Science and Information Technology, Anhui UniversitySchool of Marine Science and Technology, Northwestern Polytechnical UniversitySchool of Marine Science and Technology, Northwestern Polytechnical UniversityXi’an Precision Machinery Research InstituteAbstract Numerous surrogate-assisted evolutionary algorithms are developed for multi-objective expensive problems with low dimensions, but scarce works have paid attention to that with high dimensions, i.e., generally more than 30 decision variables. In this paper, we propose a multi-mode radial basis functions-assisted evolutionary algorithm (MMRAEA) for solving high-dimensional expensive multi-objective optimization problems. To improve the reliability, the proposed algorithm uses radial basis functions based on three modes to cooperate to provide the qualities and uncertainty information of candidate solutions. Meanwhile, bi-population based on competitive swarm optimizer and genetic algorithm are applied for better exploration and exploitation in high-dimensional search space. Accordingly, an infill criterion based on multi-mode of radial basis functions that comprehensively considers the quality and uncertainty of candidate solutions is proposed. Experimental results on widely-used benchmark problems with up to 100 decision variables demonstrate the effectiveness of our proposal. Furthermore, the proposed method is applied to the structure optimization of the blended-wing-body underwater glider (BWBUG) and gets impressive solutions.https://doi.org/10.1007/s40747-024-01737-0Multi-objective optimization problemHigh-dimensionalExpensive optimizationSurrogate ensembleStructure design of BWBUG |
| spellingShingle | Jiangtao Shen Xinjing Wang Ruixuan He Ye Tian Wenxin Wang Peng Wang Zhiwen Wen Optimization of high-dimensional expensive multi-objective problems using multi-mode radial basis functions Complex & Intelligent Systems Multi-objective optimization problem High-dimensional Expensive optimization Surrogate ensemble Structure design of BWBUG |
| title | Optimization of high-dimensional expensive multi-objective problems using multi-mode radial basis functions |
| title_full | Optimization of high-dimensional expensive multi-objective problems using multi-mode radial basis functions |
| title_fullStr | Optimization of high-dimensional expensive multi-objective problems using multi-mode radial basis functions |
| title_full_unstemmed | Optimization of high-dimensional expensive multi-objective problems using multi-mode radial basis functions |
| title_short | Optimization of high-dimensional expensive multi-objective problems using multi-mode radial basis functions |
| title_sort | optimization of high dimensional expensive multi objective problems using multi mode radial basis functions |
| topic | Multi-objective optimization problem High-dimensional Expensive optimization Surrogate ensemble Structure design of BWBUG |
| url | https://doi.org/10.1007/s40747-024-01737-0 |
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