Doğuş Üniversitesi Dergisi

Doğuş Üniversitesi Dergisi

Optimisation of Economic Order Quantity Using Neural Networks Approach

Yazarlar: Martin ZIARATI, Osman Nuri UÇAN, Reza ZIARATI

Cilt 2 , Sayı 1 , 2001 , Sayfalar -

Konular:-

Anahtar Kelimeler:Artificial Neural Network (ANN),Economic Order Quantity (EOQ)

Özet: In this paper, a Back Propagation-Artificial Neural Network (BP-ANN) has been adapted for predicting the required car parts quantities in a real and major auto parts supplier chain. The conventional approach to determine the parts requirements is the Economic Order Quantity (EOQ) method. The ability of neural models to learn, particularly their capability of handling large amounts of data simultaneously as well as their fast response time, are the characteristics desired for predictive and forecasting purposes. Here, the actual data obtained from a major auto parts supplier chain, involving a multi-layer system of supplying auto parts to car dealers, have been used to optimise and develop a BP-ANN model. The model has shown promising results in predicting parts orders with high degree of accuracy.

ATIFLAR
Atıf Yapan Eserler
Henüz Atıf Yapılmamıştır
KAYNAK GÖSTER
BibTex
KOPYALA
@article{2001, title={Optimisation of Economic Order Quantity Using Neural Networks Approach}, volume={2}, publisher={Doğuş Üniversitesi Dergisi}, author={Martin ZIARATI, Osman Nuri UÇAN, Reza ZIARATI}, year={2001} }
APA
KOPYALA
Martin ZIARATI, Osman Nuri UÇAN, Reza ZIARATI. (2001). Optimisation of Economic Order Quantity Using Neural Networks Approach (Vol. 2). Vol. 2. Doğuş Üniversitesi Dergisi.
MLA
KOPYALA
Martin ZIARATI, Osman Nuri UÇAN, Reza ZIARATI. Optimisation of Economic Order Quantity Using Neural Networks Approach. no., Doğuş Üniversitesi Dergisi, 2001.
Atıf Görüntüle
PDF Görüntüle
Kaynak Görüntüle
Paylaş
Dergi Bilgileri