Study the effect of high dimensional objective functions on multi-objective evolutionary algorithms

Basit Öğe Kaydı
dc.contributor.authorSafi, Hayder H.
dc.contributor.authorUçan, Osman Nuri
dc.contributor.authorBayat, Oğuz
dc.date.accessioned2021-05-15T12:50:04Z
dc.date.available2021-05-15T12:50:04Z
dc.date.issued2018
dc.departmentMühendislik ve Doğa Bilimleri Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.descriptionInternational Association of Researchers (IARES)
dc.description4th International Conference on Engineering and MIS, ICEMIS 2018 -- 19 June 2018 through 20 June 2018 -- -- 138526
dc.description.abstractMulti-objective Evolutionary Algorithms (MOEAs) have been widely studied by many researchers and they have been used to solve different real-world applications that have more than one objective function. However, most MOEAs work well only when the number of objective functions is small such as two or three. The performance of MOEAs starts degrading significantly when number of objective functions increases. Therefore, there is increasing importance for studying and analyzing the effect of increasing the number of objective functions on the performance of current multi objective evolutionary algorithms. In this paper, the performance of three state-of-the-art multi objective evolutionary algorithms is investigated when increasing the number of objective functions. The tested algorithms are analyzed using test DTLZ test suit. The results show that SMPSO and NSGA-II algorithms are the best two algorithms for high number of objective functions. In addition, the results show that the running time of SMPSO and GDE3 algorithms was effected and increased much when the number of objective functions is large. © Copyright 2018 ACM.en_US
dc.identifier.doi10.1145/3234698.3234763
dc.identifier.isbn9781450363921
dc.identifier.scopus2-s2.0-85052510105
dc.identifier.scopusqualityQ4
dc.identifier.urihttps://doi.org/10.1145/3234698.3234763
dc.identifier.urihttps://hdl.handle.net/20.500.12939/1176
dc.identifier.wosWOS:000694697100065
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorUçan, Osman Nuri
dc.institutionauthorBayat, Oğuz
dc.institutionauthorSafi, Hayder H.
dc.language.isoen
dc.publisherAssociation for Computing Machineryen_US
dc.relation.ispartofACM International Conference Proceeding Series
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectDifferential Evolution Algorithmen_US
dc.subjectEvolutionary Algorithmsen_US
dc.subjectMulti-Objective Problemsen_US
dc.subjectNSGA-IIen_US
dc.subjectPSOen_US
dc.titleStudy the effect of high dimensional objective functions on multi-objective evolutionary algorithms
dc.typeConference Object

Dosyalar

Koleksiyon

Scopus İndeksli Yayınlar Koleksiyonu
Bilgisayar Mühendisliği Bölümü Koleksiyonu
WoS İndeksli Yayınlar Koleksiyonu