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dc.contributor.authorEl-Abd, Mohammed
dc.description.abstractIn this paper, we test the performance of hybrid cooperative co-evolution (hCC) on the CEC15 benchmarks. In its initial stage, the method applies the recently introduced differential grouping to learn the problem variables’ inter-dependencies and separate the variables into groups of separable and non-separable ones. In its second stage, the method adopts different algorithms within the cooperative co-evolution (CC) framework to simultaneously optimize the generated groups. Results are reported for all required problem sizes.
dc.relation.journalIEEE Congress on Evolutionary Computation, CEC
dc.titleHybrid Cooperative Co-evolution for the CEC15 Benchmarks
dc.typeConference Paper
dcterms.bibliographicCitationEl-Abd, Mohammed. 'Hybrid Cooperative Co-evolution for the CEC15 Benchmarks." In the IEEE Congress on Evolutionary Computation, CEC, pp. 1053-1058, 2015

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