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Establishment of the Optimized Production Performance Detection Model with the Combination of GA and BPN


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Abstract

As the activities to improve the process rationalization, optimized production assists the enterprises to improve the production and management processes, product quality, productivity and customer service efficiency. This study analyzed the data collected from the experiments made by a lean production simulation laboratory at a university in Taiwan, so as to investigate whether production optimization results of the enterprises can promote the overall performance of production and service. This study first compared the data envelopment analysis (DEA) with the experimental data, so as to evaluate whether the optimized production can improve the performance. It then analyzed main factors influencing the income with decision tree, and established the optimized production performance detection model respectively using three data mining technologies, namely the GABPN, BPN and decision tree. The analytic results showed that the output through optimized production does improve the overall performance of production and service. The main factors affecting the technical efficiency include the time consumed from serving all dishes on the table to leaving the table and the time consumed from leaving the table to paying the bill. Among these three data mining technologies, GABPN has the best detection ability.


Keywords


Pages

Total Pages: 10
Pages: 97-106

DOI
10.1080/10798587.2014.934042


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Published

Volume: 21
Issue: 1
Year: 2014

Cite this document


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JOURNAL INFORMATION


ISSN PRINT: 1079-8587
ISSN ONLINE: 2326-005X
DOI PREFIX: 10.31209
10.1080/10798587 with T&F
IMPACT FACTOR: 0.652 (2017/2018)

TWO YEAR CITATIONS PER DOCUMENT (SJR DATA): 0.993 (2018)
SJR: "The two years line is equivalent to journal impact factor ™ (Thomson Reuters) metric."





Journal: 1995-Present


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