OPTIMISATION OF ECONOMIC ORDER QUANTITY USING NEURAL NETWORKS APPROACH

Martin Zıaratı; Osman Nuri Uçan; Reza Zıaratı

TR EN

OPTIMISATION OF ECONOMIC ORDER QUANTITY USING NEURAL NETWORKS APPROACH

Öz

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.

Anahtar Kelimeler

Artificial Neural Network (ANN), Economic Order Quantity (EOQ)

Kaynakça

ZIARATI, M (2000), "Improving the Supply Chain in the Automotive Industry Using Kaizen Engineering" MPhil transfer report, De Montfort University, UK.
HAYKIN,S. (1999), " Neural Networks"John Wiley Pub.

Ayrıntılar

Birincil Dil

İngilizce

Konular

-

Bölüm

-

Yazarlar

Martin Zıaratı Bu kişi benim

Osman Nuri Uçan Bu kişi benim

Reza Zıaratı Bu kişi benim

Yayımlanma Tarihi

1 Ocak 2001

Gönderilme Tarihi

-

Kabul Tarihi

-

Yayımlandığı Sayı

Yıl 2001 Cilt: 2 Sayı: 1

IZ

https://izlik.org/JA57TA88WT

Kaynak Göster

RIS / Bibtex

APA

Zıaratı, M., Uçan, O. N., & Zıaratı, R. (2001). OPTIMISATION OF ECONOMIC ORDER QUANTITY USING NEURAL NETWORKS APPROACH. Doğuş Üniversitesi Dergisi, 2(1), 120-128. https://izlik.org/JA57TA88WT

AMA

1.Zıaratı M, Uçan ON, Zıaratı R. OPTIMISATION OF ECONOMIC ORDER QUANTITY USING NEURAL NETWORKS APPROACH. DOUJ. 2001;2(1):120-128. https://izlik.org/JA57TA88WT

Chicago

Zıaratı, Martin, Osman Nuri Uçan, ve Reza Zıaratı. 2001. “OPTIMISATION OF ECONOMIC ORDER QUANTITY USING NEURAL NETWORKS APPROACH”. Doğuş Üniversitesi Dergisi 2 (1): 120-28. https://izlik.org/JA57TA88WT.

EndNote

Zıaratı M, Uçan ON, Zıaratı R (01 Ocak 2001) OPTIMISATION OF ECONOMIC ORDER QUANTITY USING NEURAL NETWORKS APPROACH. Doğuş Üniversitesi Dergisi 2 1 120–128.

IEEE

[1]M. Zıaratı, O. N. Uçan, ve R. Zıaratı, “OPTIMISATION OF ECONOMIC ORDER QUANTITY USING NEURAL NETWORKS APPROACH”, DOUJ, c. 2, sy 1, ss. 120–128, Oca. 2001, [çevrimiçi]. Erişim adresi: https://izlik.org/JA57TA88WT

ISNAD

Zıaratı, Martin - Uçan, Osman Nuri - Zıaratı, Reza. “OPTIMISATION OF ECONOMIC ORDER QUANTITY USING NEURAL NETWORKS APPROACH”. Doğuş Üniversitesi Dergisi 2/1 (01 Ocak 2001): 120-128. https://izlik.org/JA57TA88WT.

JAMA

1.Zıaratı M, Uçan ON, Zıaratı R. OPTIMISATION OF ECONOMIC ORDER QUANTITY USING NEURAL NETWORKS APPROACH. DOUJ. 2001;2:120–128.

MLA

Zıaratı, Martin, vd. “OPTIMISATION OF ECONOMIC ORDER QUANTITY USING NEURAL NETWORKS APPROACH”. Doğuş Üniversitesi Dergisi, c. 2, sy 1, Ocak 2001, ss. 120-8, https://izlik.org/JA57TA88WT.

Vancouver

1.Martin Zıaratı, Osman Nuri Uçan, Reza Zıaratı. OPTIMISATION OF ECONOMIC ORDER QUANTITY USING NEURAL NETWORKS APPROACH. DOUJ [Internet]. 01 Ocak 2001;2(1):120-8. Erişim adresi: https://izlik.org/JA57TA88WT