A tabu search algorithm for the training of neural networks

dc.contributor.authorDengiz, B.
dc.contributor.authorAlabas-Uslu, C.
dc.contributor.authorDengiz, O.
dc.date.accessioned2024-07-12T21:51:34Z
dc.date.available2024-07-12T21:51:34Z
dc.date.issued2009en_US
dc.departmentMaltepe Üniversitesien_US
dc.description.abstractThe most widely used training algorithm of neural networks (NNs) is back propagation ( BP), a gradient-based technique that requires significant computational effort. Metaheuristic search techniques such as genetic algorithms, tabu search (TS) and simulated annealing have been recently used to cope with major shortcomings of BP such as the tendency to converge to a local optimal and a slow convergence rate. In this paper, an efficient TS algorithm employing different strategies to provide a balance between intensification and diversification is proposed for the training of NNs. The proposed algorithm is compared with other metaheuristic techniques found in literature using published test problems, and found to outperform them in the majority of the test cases.en_US
dc.identifier.doi10.1057/palgrave.jors.2602535
dc.identifier.endpage291en_US
dc.identifier.issn0160-5682
dc.identifier.issue2en_US
dc.identifier.scopus2-s2.0-58449100709en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage282en_US
dc.identifier.urihttps://dx.doi.org/10.1057/palgrave.jors.2602535
dc.identifier.urihttps://hdl.handle.net/20.500.12415/8281
dc.identifier.volume60en_US
dc.identifier.wosWOS:000262581600014en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoenen_US
dc.publisherPALGRAVE MACMILLAN LTDen_US
dc.relation.ispartofJOURNAL OF THE OPERATIONAL RESEARCH SOCIETYen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmzKY02068
dc.subjectneural networksen_US
dc.subjectsupervised trainingen_US
dc.subjectheuristicsen_US
dc.subjecttabu searchen_US
dc.subjectsimulated annealingen_US
dc.subjectgenetic algorithmsen_US
dc.titleA tabu search algorithm for the training of neural networksen_US
dc.typeArticle
dspace.entity.typePublication

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