TOPCUOĞLU, HALUK RAHMİ2023-04-192023-04-192023-07-01Sahmoud S., TOPCUOĞLU H. R., "Dynamic multi-objective evolutionary algorithms in noisy environments", Information Sciences, cilt.634, ss.650-664, 20230020-0255https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85151471779&origin=inwardhttps://hdl.handle.net/11424/288790Real-world multi-objective optimization problems encounter different types of uncertainty that may affect the quality of solutions. One common type is the stochastic noise that contaminates the objective functions. Another type of uncertainty is the different forms of dynamism including changes in the objective functions. Although related work in the literature targets only a single type, in this paper, we study Dynamic Multi-objective Optimization problems (DMOPs) contaminated with stochastic noises by dealing with the two types of uncertainty simultaneously. In such problems, handling uncertainty becomes a critical issue since the evolutionary process should be able to distinguish between changes that come from noise and real environmental changes that resulted from different forms of dynamism. To study both noisy and dynamic environments, we propose a flexible mechanism to incorporate noise into the DMOPs. Two novel techniques called Multi-Sensor Detection Mechanism (MSD) and Welford-Based Detection Mechanism (WBD) are proposed to differentiate between real change points and noise points. The proposed techniques are incorporated into a set of Dynamic Multi-objective Evolutionary Algorithms (DMOEAs) to analyze their impact. Our empirical study reveals the effectiveness of the proposed techniques for isolating noise from real dynamic changes and diminishing the noise effect on performance.enginfo:eu-repo/semantics/openAccessSosyal ve Beşeri BilimlerSosyolojiKütüphanecilikBilgi Sistemleri, Haberleşme ve Kontrol MühendisliğiKontrol ve Sistem MühendisliğiBilgisayar BilimleriAlgoritmalarBiyoenformatikVeritabanı ve Veri YapılarıMühendislik ve TeknolojiSocial Sciences and HumanitiesSociologyLibrary SciencesInformation Systems, Communication and Control EngineeringControl and System EngineeringComputer SciencesalgorithmsbioinformaticsDatabase and Data StructuresEngineering and TechnologyMühendislik, Bilişim ve Teknoloji (ENG)Sosyal Bilimler (SOC)Bilgisayar BilimiMühendislikSosyal Bilimler GenelOTOMASYON & KONTROL SİSTEMLERİBİLGİSAYAR BİLİMİ, YAPAY ZEKABİLGİSAYAR BİLİMİ, TEORİ VE YÖNTEMBİLGİSAYAR BİLİMİ, YAZILIM MÜHENDİSLİĞİBİLGİ BİLİMİ VE KÜTÜPHANE BİLİMİEngineering, Computing & Technology (ENG)Social Sciences (SOC)COMPUTER SCIENCEENGINEERINGSOCIAL SCIENCES, GENERALAUTOMATION & CONTROL SYSTEMSCOMPUTER SCIENCE, ARTIFICIAL INTELLIGENCECOMPUTER SCIENCE, THEORY & METHODSCOMPUTER SCIENCE, SOFTWARE ENGINEERINGINFORMATION SCIENCE & LIBRARY SCIENCETeorik Bilgisayar BilimiFizik BilimleriYazılımBilgisayar Bilimi UygulamalarıBilgi Sistemleri ve YönetimiSosyal Bilimler ve Beşeri BilimlerYapay ZekaTheoretical Computer SciencePhysical SciencesSoftwareControl and Systems EngineeringComputer Science ApplicationsInformation Systems and ManagementSocial Sciences & HumanitiesArtificial IntelligenceChange detectionDynamic multi-objective optimization problemsNoise detectionNoisy optimization problemsUncertaintyarticle63465066410.1016/j.ins.2023.03.094