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A new prediction-based algorithm for dynamic multi-objective optimization problems

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dc.contributor.authorTOPCUOĞLU, HALUK RAHMİ
dc.contributor.authorsKarkazan K., TOPCUOĞLU H. R., Sahmoud S.
dc.date.accessioned2023-05-29T10:17:35Z
dc.date.available2023-05-29T10:17:35Z
dc.date.issued2023-01-01
dc.description.abstractThe mechanism for reacting to the changes in an environment when detected is the key issue that distinguishes various algorithms proposed for dynamic multi-objective optimization problems (DMOPs). The severity of change is a significant approach to identify the dynamic characteristics of DMOPs. In this paper, a prediction-based strategy based on utilizing the degree of the changes is presented to address environmental changes. In case of a change detection in the given DMOP, the severity of change is evaluated and an appropriate reaction mechanism is followed based on the degree of the observed change. To accelerate the convergence process, the algorithm may respond multiple times for the same change. The performance of our algorithm is evaluated by comparing it with dynamic multi-objective evolutionary algorithms using six benchmarks. The effectiveness of our algorithm is demonstrated in the experimental study where it outperforms other compared algorithms in most of the tested instances considered.
dc.identifier.citationKarkazan K., TOPCUOĞLU H. R., Sahmoud S., \"A New Prediction-Based Algorithm for Dynamic Multi-objective Optimization Problems\", 26th International Conference on Applications of Evolutionary Computation, EvoApplications 2023, held as part of EvoStar 2023, Brno, Çek Cumhuriyeti, 12 - 14 Nisan 2023, cilt.13989 LNCS, ss.194-209
dc.identifier.doi10.1007/978-3-031-30229-9_13
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85159409430&origin=inward
dc.identifier.urihttps://hdl.handle.net/11424/289741
dc.language.isoeng
dc.relation.ispartof26th International Conference on Applications of Evolutionary Computation, EvoApplications 2023, held as part of EvoStar 2023
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectBilgisayar Bilimleri
dc.subjectBiyoenformatik
dc.subjectMühendislik ve Teknoloji
dc.subjectComputer Sciences
dc.subjectbioinformatics
dc.subjectEngineering and Technology
dc.subjectMühendislik, Bilişim ve Teknoloji (ENG)
dc.subjectBilgisayar Bilimi
dc.subjectBİLGİSAYAR BİLİMİ, TEORİ VE YÖNTEM
dc.subjectEngineering, Computing & Technology (ENG)
dc.subjectCOMPUTER SCIENCE
dc.subjectCOMPUTER SCIENCE, THEORY & METHODS
dc.subjectTeorik Bilgisayar Bilimi
dc.subjectFizik Bilimleri
dc.subjectGenel Bilgisayar Bilimi
dc.subjectTheoretical Computer Science
dc.subjectPhysical Sciences
dc.subjectGeneral Computer Science
dc.subjectchange detection
dc.subjectdynamic multi-objective optimization
dc.subjectprediction-based optimization
dc.subjectseverity of change
dc.titleA new prediction-based algorithm for dynamic multi-objective optimization problems
dc.typeconferenceObject
dspace.entity.typePublication
local.avesis.idf72aa173-6d1e-4a96-b520-40ddb6568c91
local.indexed.atSCOPUS
relation.isAuthorOfPublication54c6a927-2146-44b3-90ee-33dac6503317
relation.isAuthorOfPublication.latestForDiscovery54c6a927-2146-44b3-90ee-33dac6503317

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