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Uniform Big Bang-Chaotic Big Crunch optimization

MakaleYalnız künyeScopus SJRQ1

Özet

This study proposes methods to improve the convergence of the novel optimization method, Big Bang-Big Crunch (BB-BC). Uniform population method has been used to generate uniformly distributed random points in the Big Bang phase. Chaos has been utilized to rapidly shrink those points to a single representative point via a center of mass in the Big Crunch phase. The proposed algorithm has been named as Uniform Big Bang-Chaotic Big Crunch (UBB-CBC). The performance of the UBB-CBC optimization algorithm demonstrates superiority over the BB-BC optimization for the benchmark functions. (C) 2010 Elsevier B.V. All rights reserved.

Anahtar Kelimeler

Big Bang-Big Crunch optimizationChaosMetaheuristic optimizationSoft computingUniform population
RDL Kalıcı Bağlantı (PID)
https://rdlopen.rawdatalibrary.net/r/munzur/4572Resmi atıflarda kullanılan kalıcı adres
DOI
https://doi.org/10.1016/j.cnsns.2010.12.025Yayıncı resmi DOI adresi
İndeks kayıtları
Web of ScienceWeb of Science
Kaydın indeks veri tabanlarındaki sayfası (aktarımda alınan kayıt numarasıyla). Erişim, indeksin kendi koşullarına bağlıdır.
Atıflar
WoS
48
OpenAlex
62
Her kaynağın kendi saydığı toplam atıf; aktarım ve zenginleştirme sırasında alındı.
Tam Kayıt
AlanDeğerDil
dc.contributor.authorAlatas, Bilal
dc.date.accessioned2026-10-28T15:03:28.534718204Z
dc.date.available2026-10-28T15:03:28.534718204Z
dc.date.issued2011-09
dc.description.abstractThis study proposes methods to improve the convergence of the novel optimization method, Big Bang-Big Crunch (BB-BC). Uniform population method has been used to generate uniformly distributed random points in the Big Bang phase. Chaos has been utilized to rapidly shrink those points to a single representative point via a center of mass in the Big Crunch phase. The proposed algorithm has been named as Uniform Big Bang-Chaotic Big Crunch (UBB-CBC). The performance of the UBB-CBC optimization algorithm demonstrates superiority over the BB-BC optimization for the benchmark functions. (C) 2010 Elsevier B.V. All rights reserved.
dc.identifier.doi10.1016/j.cnsns.2010.12.025
dc.identifier.eissn1878-7274
dc.identifier.endpage3703
dc.identifier.issn1007-5704
dc.identifier.issue9
dc.identifier.startpage3696
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/munzur/4572
dc.identifier.volume16
dc.identifier.wosWOS:000290368700028
dc.language.isoen
dc.publisherELSEVIER
dc.relation.ispartofCOMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectBig Bang-Big Crunch optimization
dc.subjectChaos
dc.subjectMetaheuristic optimization
dc.subjectSoft computing
dc.subjectUniform population
dc.subject.classificationMathematics, Applied
dc.subject.classificationMathematics, Interdisciplinary Applications
dc.subject.classificationMechanics
dc.subject.classificationPhysics, Fluids & Plasmas
dc.subject.classificationPhysics, Mathematical
dc.subject.classificationMathematics
dc.subject.classificationPhysics
dc.subject.otherSWARM OPTIMIZATION
dc.subject.otherALGORITHM
dc.subject.otherDESIGN
dc.titleUniform Big Bang-Chaotic Big Crunch optimization
dc.typeArticle
rdl.citation.openalex62
rdl.citation.wos48
rdl.oa.statusclosed
rdl.scopus.quartileQ1
rdl.source.indexWOS
rdl.wos.indexScience Citation Index Expanded (SCI-EXPANDED)