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Exploiting characterization of dynamism for enhancing dynamic multi-objective evolutionary algorithms

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dc.contributor.authorTOPCUOĞLU, HALUK RAHMİ
dc.contributor.authorsSahmoud, Shaaban; Topcuoglu, Haluk Rahmi
dc.date.accessioned2022-03-12T22:27:57Z
dc.date.available2022-03-12T22:27:57Z
dc.date.issued2019
dc.description.abstractCharacterization of dynamism is an essential phase for some of the dynamic multi-objective evolutionary algorithms (DMOEAs) in order to improve their performance. Although frequency of change and severity of change are the two main perspectives of characterizing dynamic features of the dynamic multi-objective optimization problems (DMOPs), they do not sufficiently attract attentions of the research community. In this paper, we propose a set of new sensor-based change detection schemes for the DMOPs that significantly outperform the current used change detection schemes. Additionally, a new technique is proposed for detecting the change severity for DMOPs. The experimental evaluation based on different test problems and change severity levels validates performance of our technique. We also propose a novel adaptive algorithm called change-responsive NSGA-II (CR-NSGA-II) algorithm that incorporates the change detection schemes, the technique for change severity and a new response mechanism into the NSGA-II algorithm. Our algorithm demonstrates competitive and significantly better results than the leading DMOEAs on majority of test problems and metrics considered. (C) 2019 Elsevier B.V. All rights reserved.
dc.identifier.doi10.1016/j.asoc.2019.105783
dc.identifier.eissn1872-9681
dc.identifier.issn1568-4946
dc.identifier.urihttps://hdl.handle.net/11424/235264
dc.identifier.wosWOS:000500691600063
dc.language.isoeng
dc.publisherELSEVIER
dc.relation.ispartofAPPLIED SOFT COMPUTING
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectDynamic multi-objective optimization problems
dc.subjectDynamic multi-objective evolutionary algorithms
dc.subjectChange detection
dc.subjectCharacterization of change
dc.subjectOPTIMIZATION
dc.titleExploiting characterization of dynamism for enhancing dynamic multi-objective evolutionary algorithms
dc.typearticle
dspace.entity.typePublication
local.avesis.id9030375b-b8ea-4af2-9289-21dc293059b8
local.import.packageSS17
local.indexed.atWOS
local.indexed.atSCOPUS
local.journal.articlenumber105783
local.journal.numberofpages18
local.journal.quartileQ1
oaire.citation.titleAPPLIED SOFT COMPUTING
oaire.citation.volume85
relation.isAuthorOfPublication54c6a927-2146-44b3-90ee-33dac6503317
relation.isAuthorOfPublication.latestForDiscovery54c6a927-2146-44b3-90ee-33dac6503317

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