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dc.contributor.authorJiang, Shouyongen
dc.contributor.authorYang, Shengxiangen
dc.contributor.authorWang, Yongen
dc.contributor.authorLiu, Xiaobinen
dc.date.accessioned2017-05-31T13:56:56Z
dc.date.available2017-05-31T13:56:56Z
dc.date.issued2017
dc.identifier.citationJiang, S., Yang, S., Wang, Y. and Liu, X. (2017) Scalarizing functions in decomposition-based multiobjective evolutionary algorithms. IEEE Transactions on Evolutionary Computation, in pressen
dc.identifier.urihttp://hdl.handle.net/2086/14214
dc.description.abstractDecomposition-based multiobjective evolutionary algorithms have received increasing research interests due to their high performance for solving multiobjective optimization problems. However, scalarizing functions, which play a crucial role in balancing diversity and convergence in these kinds of algorithms, have not been fully investigated. This paper is mainly devoted to presenting two new scalarizing functions and analyzing their effect in decomposition-based multiobjective evolutionary algorithms. Additionally, we come up with an efficient framework for decomposition-based multiobjective evolutionary algorithms based on the proposed scalarizing functions and some new strategies. Extensive experimental studies have demonstrated the effectiveness of the proposed scalarizing functions and algorithm.en
dc.language.isoen_USen
dc.publisherIEEE Pressen
dc.subjectMultiobjective optimizationen
dc.subjectScalarizing functionen
dc.subjectDecompositionen
dc.subjectEvolutionary algorithmen
dc.titleScalarizing functions in decomposition-based multiobjective evolutionary algorithmsen
dc.typeArticleen
dc.identifier.doihttps://doi.org/10.1109/tevc.2017.2707980
dc.identifier.doi
dc.researchgroupCentre for Computational Intelligenceen
dc.peerreviewedYesen
dc.explorer.multimediaNoen
dc.funderEngineering and Physical Sciences Research Council (EPSRC)en
dc.funderNational Natural Science Foundation of China (NSFC)en
dc.funderEU Horizon 2020 Marie Sklodowska-Curie Individual Fellowshipsen
dc.projectidEP/K001310/1en
dc.projectid61673331 and 61673397en
dc.projectid661327en
dc.cclicenceCC-BY-NCen
dc.date.acceptance2017-05-05en
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en


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