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dc.contributor.authorZou, Juan
dc.contributor.authorFu, Liuwei
dc.contributor.authorYang, Shengxiang
dc.contributor.authorZheng, Jinhua
dc.contributor.authorRuan, Gan
dc.contributor.authorPei, Tingrui
dc.contributor.authorWang, Lei
dc.date.accessioned2019-04-16T09:22:08Z
dc.date.available2019-04-16T09:22:08Z
dc.date.issued2019-03-11
dc.identifier.citationZou, J., Fu, L., Yang, S., Zheng, J., Ruan, G., Pei, T. and Wang, L. (2019) An adaptation reference-point-based multiobjective evolutionary algorithm. Information Sciences, 488, pp. 41-57.en
dc.identifier.urihttps://www.dora.dmu.ac.uk/handle/2086/17717
dc.descriptionThe file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.en
dc.description.abstractIt is well known that maintaining a good balance between convergence and diversity is crucial to the performance of multiobjective optimization algorithms (MOEAs). However, the Pareto front (PF) of multiobjective optimization problems (MOPs) affects the performance of MOEAs, especially reference point-based ones. This paper proposes a reference-point-based adaptive method to study the PF of MOPs according to the candidate solutions of the population. In addition, the proportion and angle function presented selects elites during environmental selection. Compared with five state-of-the-art MOEAs, the proposed algorithm shows highly competitive effectiveness on MOPs with six complex characteristics.en
dc.language.isoen_USen
dc.publisherElsevieren
dc.subjectMultiobjective optimizationen
dc.subjectMany-objective optimizationen
dc.subjectEvolutionary algorithmsen
dc.subjectGenetic algorithmsen
dc.titleAn adaptation reference-point-based multiobjective evolutionary algorithmen
dc.typeArticleen
dc.identifier.doihttps://doi.org/10.1016/j.ins.2019.03.020
dc.peerreviewedYesen
dc.funderOther external funder (please detail below)en
dc.projectid61876164en
dc.projectid61673331en
dc.projectid61772178en
dc.cclicenceCC-BY-NCen
dc.date.acceptance2019-03-09
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en
dc.funder.otherNational Natural Science Foundation of Chinaen
dc.funder.otherNational Natural Science Foundation of Chinaen
dc.funder.otherNational Natural Science Foundation of Chinaen


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