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• W2088337922 abstract "Cooperative Co-evolutionary algorithms are effective approaches to solve large-scale optimization problems. The crucial challenge in these methods is the design of a decomposition method which is able to detect interactions among variables. In this paper, we proposed a decomposition method based on High Dimensional Model Representation (HDMR) which extracts separable and nonseparable subcomponents for Cooperative Co-evolutionary algorithms. The entire decomposition procedure is conducted before applying the optimization. The experimental results for D=1000 on twenty CEC-2010 benchmark functions show that the proposed method is promisingly efficient to solve large-scale optimization problems. The proposed approach is compared with two other methods and discussed in details." @default.
• W2088337922 created "2016-06-24" @default.
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• W2088337922 date "2014-07-01" @default.
• W2088337922 modified "2023-10-13" @default.
• W2088337922 title "Cooperative Co-evolution with a new decomposition method for large-scale optimization" @default.
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• W2088337922 doi "https://doi.org/10.1109/cec.2014.6900327" @default.
• W2088337922 hasPublicationYear "2014" @default.
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