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A neural network model for solving the lot-sizing problem Lot ®
| Content Provider | Semantic Scholar |
|---|---|
| Author | Gaafar, Khadiga M. Choueiki, M. Hisham |
| Copyright Year | 2015 |
| Abstract | Arti®cial neural network models have been used successfully to solve demand forecasting and production scheduling problems; the two steps that typically precede and s쳮d Material Requirements Planning (MRP). In this paper, a neural network model is applied to the MRP problem of lot-sizing. The model's performance is evaluated under dierent scenarios and is compared to common heuristics that address the same problem. Results show that the developed arti®cial neural network model is capable of solving the lot-sizing problem with notable consistency and reasonable accuracy. # 2000 Elsevier Science Ltd. All rights reserved. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://isiarticles.com/bundles/Article/pre/pdf/22664.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
