A neural network model for scheduling problems

dc.citation.epage299en_US
dc.citation.issueNumber2en_US
dc.citation.spage288en_US
dc.citation.volumeNumber93en_US
dc.contributor.authorSabuncuoğlu, İ.en_US
dc.contributor.authorGurgun, B.en_US
dc.date.accessioned2016-02-08T10:50:17Z
dc.date.available2016-02-08T10:50:17Z
dc.date.issued1996en_US
dc.departmentDepartment of Industrial Engineeringen_US
dc.description.abstractArtificial neural networks (ANNs) have been successfully applied to solve a variety of problems. This paper proposes a new neural network approach to solve the single machine mean tardiness scheduling problem and the minimum makespan job shop scheduling problem. The proposed network combines the characteristics of neural networks and algorithmic approaches. The performance of the network is compared with the existing scheduling algorithms under various experimental conditions. A comprehensive bibliography is also provided in the paper.en_US
dc.description.provenanceMade available in DSpace on 2016-02-08T10:50:17Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 1996en
dc.identifier.doi10.1016/0377-2217(96)00041-0en_US
dc.identifier.issn0377-2217
dc.identifier.urihttp://hdl.handle.net/11693/25777
dc.language.isoEnglishen_US
dc.publisherElsevieren_US
dc.relation.isversionofhttp://dx.doi.org/10.1016/0377-2217(96)00041-0en_US
dc.source.titleEuropean Journal of Operational Researchen_US
dc.subjectNeural networksen_US
dc.subjectSchedulingen_US
dc.subjectAlgorithmsen_US
dc.subjectComputer simulationen_US
dc.subjectMachineryen_US
dc.subjectOptimizationen_US
dc.subjectProductionen_US
dc.subjectSchedulingen_US
dc.subjectSurveysen_US
dc.subjectMachine mean tardiness scheduling problemen_US
dc.subjectMinimum makespan job shop scheduling problemen_US
dc.subjectNeural network modelen_US
dc.subjectNeural networksen_US
dc.titleA neural network model for scheduling problemsen_US
dc.typeArticleen_US

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