Optimization of manufacturing systems using a neural network metamodel with a new training approach

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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.abstractIn this study, two manufacturing systems, a kanban-controlled system and a multi-stage, multi-server production line in a diamond tool production system, are optimized utilizing neural network metamodels (tst_NNM) trained via tabu search (TS) which was developed previously by the authors. The most widely used training algorithm for neural networks has been back propagation which is based on a gradient technique that requires significant computational effort. To deal with the major shortcomings of back propagation (BP) such as the tendency to converge to a local optimal and a slow convergence rate, the TS metaheuristic method is used for the training of artificial neural networks to improve the performance of the metamodelling approach. The metamodels are analysed based on their ability to predict simulation results versus traditional neural network metamodels that have been trained by BP algorithm (bp NNM). Computational results show that tst NNM is superior to bp NNM for both of the manufacturing systems. Journal of the Operational Research Society (2009) 60, 1191-1197. doi:10.1057/palgrave.jors.2602620 Published online 30 July 2008en_US
dc.identifier.doi10.1057/palgrave.jors.2602620
dc.identifier.endpage1197en_US
dc.identifier.issn0160-5682
dc.identifier.issue9en_US
dc.identifier.scopus2-s2.0-68649087846en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage1191en_US
dc.identifier.urihttps://dx.doi.org/10.1057/palgrave.jors.2602620
dc.identifier.urihttps://hdl.handle.net/20.500.12415/8282
dc.identifier.volume60en_US
dc.identifier.wosWOS:000268641100006en_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.snmzKY02069
dc.subjectsimulationen_US
dc.subjectmetamodelen_US
dc.subjectsimulation optimizationen_US
dc.subjectneural networksen_US
dc.subjecttabu searchen_US
dc.titleOptimization of manufacturing systems using a neural network metamodel with a new training approachen_US
dc.typeArticle
dspace.entity.typePublication

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