An investigation into the applicability of neural networks to multi-performance measure dispatching in a dynamic, single machine shop

dc.contributor.authorMitlehner, Michael M.en
dc.contributor.departmentIndustrial and Systems Engineeringen
dc.date.accessioned2022-11-09T06:28:00Zen
dc.date.available2022-11-09T06:28:00Zen
dc.date.issued1994en
dc.description.abstractThis thesis investigates the applicability of backpropagation neural networks to production order dispatching in a dynamic, single machine shop where the achievement of multiple performance measures is desired. There has been relatively little research done in this area so the objectives center around the determination of information and parameters which lead to improved network performance with respect to learning as well as decision making. Results of the research showed that many of the qualities inherent to backpropagation neural networks were compatible with the requirements of the dispatching activity. The networks that were trained and tested had the ability to implicitly map the complex functional relationships between inputs reflecting system status and desired performance and outputs which represented appropriate coefficients used to determine job priority. Once trained they displayed good generalization capabilities when exposed to information they had never been exposed to before. Most importantly, they provided the basis for a complex dispatching procedure which utilized considerable shop floor information to make completely dynamic, real time dispatching decisions. Guidelines and generalizations for similar applications were developed including: input selection and presentation formats, effective training parameters, the effect of using purely dynamic vs. historical data as shop status inputs, the effect of compromising desired performance measure inputs, and the effect of changes in the underlying shop parameters.en
dc.description.degreeM.S.en
dc.format.extentx, 179 leavesen
dc.format.mimetypeapplication/pdfen
dc.identifier.urihttp://hdl.handle.net/10919/112535en
dc.language.isoenen
dc.publisherVirginia Polytechnic Institute and State Universityen
dc.relation.isformatofOCLC# 32290663en
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subject.lccLD5655.V855 1994.M585en
dc.subject.lcshNeural networks (Computer science)en
dc.subject.lcshProduction schedulingen
dc.titleAn investigation into the applicability of neural networks to multi-performance measure dispatching in a dynamic, single machine shopen
dc.typeThesisen
dc.type.dcmitypeTexten
thesis.degree.disciplineIndustrial and Systems Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameM.S.en

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