Wang, WenjunYang, ShaoqiangLin, QiuzhenZhang, QingfuWong, Ka ChunCoello, Carlos A.CoelloChen, Jianyong2019-11-012019-11-012019-08Wang, W, Yang, S, Lin, Q, Zhang, Q, Wong, K C, Coello, C A C & Chen, J 2019, 'An Effective Ensemble Framework for Multi-Objective Optimization', IEEE Transactions on Evolutionary Computation, vol. 23, no. 4, 8519635, pp. 645-659. https://doi.org/10.1109/TEVC.2018.28790781089-778XMendeley: 03f37117-c268-3d4a-876a-b382bb873957https://hdl.handle.net/2164/13204This work was supported by the National Natural Science Foundation of China under Grants 61876110, 61876163, and 61836005, a grant from ANR/RGC Joint Research Scheme sponsored by the Research Grants Council of the Hong Kong Special Administrative Region, China and France National Research Agency (Project No. A-CityU101/16), the Joint Funds of the National Natural Science Foundation of China under Key Program Grant U1713212, and CONACyT grant no. 221551.151126908engcompetitive evolutioncooperative selection.ensemble frameworkmulti-objective optimizationmultiobjective optimizationcooperative selectionCompetitive evolutionensemble framework (EF)QA75 Electronic computers. Computer scienceSoftwareTheoretical Computer ScienceComputational Theory and MathematicsQA75Journal article10.1109/TEVC.2018.2879078http://www.scopus.com/inward/record.url?scp=85055895559&partnerID=8YFLogxKhttp://www.mendeley.com/research/effective-ensemble-framework-multiobjective-optimization234