High order neural networks to control manufacturing systems - a comparison study
- Rovithakis, George A., 1968-(http://viaf.org/viaf/116827977)
- Γαγανης Βασιλειος(http://users.isc.tuc.gr/~vgaganis)
- Gaganis Vasileios(http://users.isc.tuc.gr/~vgaganis)
- Perrakis, Stelios(http://viaf.org/viaf/65564614)
- Χριστοδουλου Μανωλης(http://users.isc.tuc.gr/~manolis)
- Christodoulou Manolis(http://users.isc.tuc.gr/~manolis)
DOI Publisher
Institute of Electrical and Electronics Engineers (IEEE)Abstract
Summarization: In this paper the neuro adaptive scheduling methodology is evaluated by comparing its performance with conventional schedulers, through simulation studies. The case study chosen constitutes an existing manufacturing cell, which can be viewed as a highly complex nonacyclic FMS, with extremely heterogenous part processing times. The results reveal superiority of our algorithm in terms of backlogging and inventory cost, system stability and work-in-processPresented on
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