A honeybees-inspired heuristic algorithm for numerical optimisation

Basit Öğe Kaydı
dc.authoridAydin, Mehmet/0000-0002-4890-5648
dc.contributor.authorDugenci, Muharrem
dc.contributor.authorAydin, Mehmet Emin
dc.date.accessioned2024-09-29T15:51:05Z
dc.date.available2024-09-29T15:51:05Z
dc.date.issued2020
dc.departmentKarabük Üniversitesien_US
dc.description.abstractSwarm intelligence is all about developing collective behaviours to solve complex, ill-structured and large-scale problems. Efficiency in collective behaviours depends on how to harmonise the individual contributors so that a complementary collective effort can be achieved to offer a useful solution. The main points in organising the harmony remain as managing the diversification and intensification actions appropriately, where the efficiency of collective behaviours depends on blending these two actions appropriately. In this paper, a hybrid bee algorithm is presented, which harmonises bee operators of two mainstream well-known swarm intelligence algorithms inspired of natural honeybee colonies. The parent algorithms have been overviewed with many respects, strengths and weaknesses are identified, first, and the hybrid version has been proposed, next. The efficiency of the hybrid algorithm is demonstrated in comparison with the parent algorithms in solving two types of numerical optimisation problems; (1) a set of well-known functional optimisation benchmark problems and (2) optimising the weights of a set of artificial neural network models trained for medical classification benchmark problems. The experimental results demonstrate the outperforming success of the proposed hybrid algorithm in comparison with two original/parent bee algorithms in solving both types of numerical optimisation benchmarks.en_US
dc.identifier.doi10.1007/s00521-019-04533-x
dc.identifier.endpage12325en_US
dc.identifier.issn0941-0643
dc.identifier.issn1433-3058
dc.identifier.issue16en_US
dc.identifier.scopus2-s2.0-85074589969en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage12311en_US
dc.identifier.urihttps://doi.org/10.1007/s00521-019-04533-x
dc.identifier.urihttps://hdl.handle.net/20.500.14619/3885
dc.identifier.volume32en_US
dc.identifier.wosWOS:000490882400001en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringer London Ltden_US
dc.relation.ispartofNeural Computing & Applicationsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectSwarm intelligenceen_US
dc.subjectNumerical optimisationen_US
dc.subjectBee-inspired algorithmsen_US
dc.subjectDiversification and intensificationen_US
dc.subjectTraining feed-forward neural networksen_US
dc.titleA honeybees-inspired heuristic algorithm for numerical optimisationen_US
dc.typeArticleen_US

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu