Job Shop Flow Time Prediction using Neural Networks
| Autor: | Pedro Neto, Pedro Coelho, Vanessa S.M. Magalhães, Vera S. G. Ribeiro, Cristóvão Silva |
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| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
0209 industrial biotechnology
Total work 021103 operations research Artificial neural network Job shop business.industry Computer science Dispatching rules Dynamic job shop 0211 other engineering and technologies 02 engineering and technology Industrial and Manufacturing Engineering Dynamic due date assignment rules 020901 industrial engineering & automation Artificial Intelligence Artificial intelligence business Flow time Simulation Artificial Neural Networks |
| Popis: | In this paper we investigate the use of Artificial Neural Networks (ANN) for flow time prediction and, consequently, to estimate due dates (DD) in a hypothetical dynamic job-shop. The effectiveness of the proposed ANN based DD assignment model is evaluated comparing it performance with the performance of two dynamic DD assignment rules proposed in the literature: Dynamic Total Work Content, and Dynamic Processing Plus Waiting. Results show that ANN based DD assignment models are more effective than, not only available static DD assignment rules, as concluded by other researchers, but also than the more effective Dynamic DD assignment rules. |
| Databáze: | OpenAIRE |
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