An Adaptive Mechanism With Cooperative Coevolution and Covariance for Differential Evolution
Differential evolution (DE) is an evolutionary algorithm widely used to solve optimization problems with different characteristics in fields where actions and decisions depend on numerical data such as engineering, economics, and logistics. In this paper, an adaptive differential evolution mechanism...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2021-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9436784/ |
| _version_ | 1798003325290938368 |
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| author | Bin Wang Lu Ren Juan Diego Prado Wenjuan He Haiyan Jin Qiaoyong Jiang Xiaofan Wang |
| author_facet | Bin Wang Lu Ren Juan Diego Prado Wenjuan He Haiyan Jin Qiaoyong Jiang Xiaofan Wang |
| author_sort | Bin Wang |
| collection | DOAJ |
| description | Differential evolution (DE) is an evolutionary algorithm widely used to solve optimization problems with different characteristics in fields where actions and decisions depend on numerical data such as engineering, economics, and logistics. In this paper, an adaptive differential evolution mechanism with cooperative co-evolution and covariance (A-CC/COV-DE) is proposed to overcome the low efficiency of differential evolution when solving large-scale numerical optimization problems, especially when the correlation between the variables of the problem is unknown. An unknown correlation of variables hinders DE from achieving an optimal search process since different types of correlations ideally require distinct optimization strategies. According to the separability of variables, the appropriate evolutionary strategy is selected adaptively. For separable functions, cooperative coevolution is adopted. After using extended differential grouping to split the problem, the sub-components are optimized by differential evolution. This reduces the dimensionality and complexity of the problem, improving its convergence speed and global search ability. For non-separable functions, a covariance matrix is calculated, and then the eigenvector is used to rotate the coordinate system. This leads to eliminate the correlation between variables and improve the search efficiency of differential evolution. We evaluated the performance of A-CC/COV-DE on the CEC 2014 test suite and compared it with state-of-the-art differential evolution algorithms. The experimental results show that our proposal is quite competitive with recent algorithms. |
| first_indexed | 2024-04-11T12:05:51Z |
| format | Article |
| id | doaj.art-0fd71789ba344816bea894c1a7d81465 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-11T12:05:51Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-0fd71789ba344816bea894c1a7d814652022-12-22T04:24:43ZengIEEEIEEE Access2169-35362021-01-019998909990410.1109/ACCESS.2021.30822029436784An Adaptive Mechanism With Cooperative Coevolution and Covariance for Differential EvolutionBin Wang0https://orcid.org/0000-0003-3524-8594Lu Ren1https://orcid.org/0000-0002-9153-3018Juan Diego Prado2https://orcid.org/0000-0002-5389-5472Wenjuan He3https://orcid.org/0000-0002-8727-1115Haiyan Jin4https://orcid.org/0000-0003-3742-4029Qiaoyong Jiang5https://orcid.org/0000-0001-9542-9739Xiaofan Wang6https://orcid.org/0000-0002-9610-6445Faculty of Computer Science and Engineering, Xi’an University of Technology, Xi’an, ChinaFaculty of Computer Science and Engineering, Xi’an University of Technology, Xi’an, ChinaFaculty of Computer Science and Engineering, Xi’an University of Technology, Xi’an, ChinaShaanxi Key Laboratory for Network Computing and Security Technology, Xi’an, ChinaFaculty of Computer Science and Engineering, Xi’an University of Technology, Xi’an, ChinaFaculty of Computer Science and Engineering, Xi’an University of Technology, Xi’an, ChinaFaculty of Computer Science and Engineering, Xi’an University of Technology, Xi’an, ChinaDifferential evolution (DE) is an evolutionary algorithm widely used to solve optimization problems with different characteristics in fields where actions and decisions depend on numerical data such as engineering, economics, and logistics. In this paper, an adaptive differential evolution mechanism with cooperative co-evolution and covariance (A-CC/COV-DE) is proposed to overcome the low efficiency of differential evolution when solving large-scale numerical optimization problems, especially when the correlation between the variables of the problem is unknown. An unknown correlation of variables hinders DE from achieving an optimal search process since different types of correlations ideally require distinct optimization strategies. According to the separability of variables, the appropriate evolutionary strategy is selected adaptively. For separable functions, cooperative coevolution is adopted. After using extended differential grouping to split the problem, the sub-components are optimized by differential evolution. This reduces the dimensionality and complexity of the problem, improving its convergence speed and global search ability. For non-separable functions, a covariance matrix is calculated, and then the eigenvector is used to rotate the coordinate system. This leads to eliminate the correlation between variables and improve the search efficiency of differential evolution. We evaluated the performance of A-CC/COV-DE on the CEC 2014 test suite and compared it with state-of-the-art differential evolution algorithms. The experimental results show that our proposal is quite competitive with recent algorithms.https://ieeexplore.ieee.org/document/9436784/Cooperative coevolutioncovariancedifferential evolutionadaptive mechanism |
| spellingShingle | Bin Wang Lu Ren Juan Diego Prado Wenjuan He Haiyan Jin Qiaoyong Jiang Xiaofan Wang An Adaptive Mechanism With Cooperative Coevolution and Covariance for Differential Evolution IEEE Access Cooperative coevolution covariance differential evolution adaptive mechanism |
| title | An Adaptive Mechanism With Cooperative Coevolution and Covariance for Differential Evolution |
| title_full | An Adaptive Mechanism With Cooperative Coevolution and Covariance for Differential Evolution |
| title_fullStr | An Adaptive Mechanism With Cooperative Coevolution and Covariance for Differential Evolution |
| title_full_unstemmed | An Adaptive Mechanism With Cooperative Coevolution and Covariance for Differential Evolution |
| title_short | An Adaptive Mechanism With Cooperative Coevolution and Covariance for Differential Evolution |
| title_sort | adaptive mechanism with cooperative coevolution and covariance for differential evolution |
| topic | Cooperative coevolution covariance differential evolution adaptive mechanism |
| url | https://ieeexplore.ieee.org/document/9436784/ |
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