Cooperative Coevolution with Two-Stage Decomposition for Large-Scale Global Optimization Problems
Cooperative coevolution (CC) is an effective framework for solving large-scale global optimization (LSGO) problems. However, CC with static decomposition method is ineffective for fully nonseparable problems, and CC with dynamic decomposition method to decompose problems is computationally costly. T...
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2021/2653807 |
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| author | H. D. Yue Y. Sun |
| author_facet | H. D. Yue Y. Sun |
| author_sort | H. D. Yue |
| collection | DOAJ |
| description | Cooperative coevolution (CC) is an effective framework for solving large-scale global optimization (LSGO) problems. However, CC with static decomposition method is ineffective for fully nonseparable problems, and CC with dynamic decomposition method to decompose problems is computationally costly. Therefore, a two-stage decomposition (TSD) method is proposed in this paper to decompose LSGO problems using as few computational resources as possible. In the first stage, to decompose problems using low computational resources, a hybrid-pool differential grouping (HPDG) method is proposed, which contains a hybrid-pool-based detection structure (HPDS) and a unit vector-based perturbation (UVP) strategy. In the second stage, to decompose the fully nonseparable problems, a known information-based dynamic decomposition (KIDD) method is proposed. Analytical methods are used to demonstrate that HPDG has lower decomposition complexity compared to state-of-the-art static decomposition methods. Experiments show that CC with TSD is a competitive algorithm for solving LSGO problems. |
| format | Article |
| id | doaj-art-bf4fb3b2d0da4b99917fc7608af3c5c2 |
| institution | Kabale University |
| issn | 1607-887X |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-bf4fb3b2d0da4b99917fc7608af3c5c22025-02-03T06:43:52ZengWileyDiscrete Dynamics in Nature and Society1607-887X2021-01-01202110.1155/2021/2653807Cooperative Coevolution with Two-Stage Decomposition for Large-Scale Global Optimization ProblemsH. D. Yue0Y. Sun1School of Computer, Electronics and InformationSchool of Computer, Electronics and InformationCooperative coevolution (CC) is an effective framework for solving large-scale global optimization (LSGO) problems. However, CC with static decomposition method is ineffective for fully nonseparable problems, and CC with dynamic decomposition method to decompose problems is computationally costly. Therefore, a two-stage decomposition (TSD) method is proposed in this paper to decompose LSGO problems using as few computational resources as possible. In the first stage, to decompose problems using low computational resources, a hybrid-pool differential grouping (HPDG) method is proposed, which contains a hybrid-pool-based detection structure (HPDS) and a unit vector-based perturbation (UVP) strategy. In the second stage, to decompose the fully nonseparable problems, a known information-based dynamic decomposition (KIDD) method is proposed. Analytical methods are used to demonstrate that HPDG has lower decomposition complexity compared to state-of-the-art static decomposition methods. Experiments show that CC with TSD is a competitive algorithm for solving LSGO problems.http://dx.doi.org/10.1155/2021/2653807 |
| spellingShingle | H. D. Yue Y. Sun Cooperative Coevolution with Two-Stage Decomposition for Large-Scale Global Optimization Problems Discrete Dynamics in Nature and Society |
| title | Cooperative Coevolution with Two-Stage Decomposition for Large-Scale Global Optimization Problems |
| title_full | Cooperative Coevolution with Two-Stage Decomposition for Large-Scale Global Optimization Problems |
| title_fullStr | Cooperative Coevolution with Two-Stage Decomposition for Large-Scale Global Optimization Problems |
| title_full_unstemmed | Cooperative Coevolution with Two-Stage Decomposition for Large-Scale Global Optimization Problems |
| title_short | Cooperative Coevolution with Two-Stage Decomposition for Large-Scale Global Optimization Problems |
| title_sort | cooperative coevolution with two stage decomposition for large scale global optimization problems |
| url | http://dx.doi.org/10.1155/2021/2653807 |
| work_keys_str_mv | AT hdyue cooperativecoevolutionwithtwostagedecompositionforlargescaleglobaloptimizationproblems AT ysun cooperativecoevolutionwithtwostagedecompositionforlargescaleglobaloptimizationproblems |