A neural network model for scheduling problems
dc.citation.epage | 299 | en_US |
dc.citation.issueNumber | 2 | en_US |
dc.citation.spage | 288 | en_US |
dc.citation.volumeNumber | 93 | en_US |
dc.contributor.author | Sabuncuoğlu, İ. | en_US |
dc.contributor.author | Gurgun, B. | en_US |
dc.date.accessioned | 2016-02-08T10:50:17Z | |
dc.date.available | 2016-02-08T10:50:17Z | |
dc.date.issued | 1996 | en_US |
dc.department | Department of Industrial Engineering | en_US |
dc.description.abstract | Artificial 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.identifier.doi | 10.1016/0377-2217(96)00041-0 | en_US |
dc.identifier.issn | 0377-2217 | |
dc.identifier.uri | http://hdl.handle.net/11693/25777 | |
dc.language.iso | English | en_US |
dc.publisher | Elsevier | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1016/0377-2217(96)00041-0 | en_US |
dc.source.title | European Journal of Operational Research | en_US |
dc.subject | Neural networks | en_US |
dc.subject | Scheduling | en_US |
dc.subject | Algorithms | en_US |
dc.subject | Computer simulation | en_US |
dc.subject | Machinery | en_US |
dc.subject | Optimization | en_US |
dc.subject | Production | en_US |
dc.subject | Scheduling | en_US |
dc.subject | Surveys | en_US |
dc.subject | Machine mean tardiness scheduling problem | en_US |
dc.subject | Minimum makespan job shop scheduling problem | en_US |
dc.subject | Neural network model | en_US |
dc.subject | Neural networks | en_US |
dc.title | A neural network model for scheduling problems | en_US |
dc.type | Article | en_US |
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