Öz
Son yıllarda, geri yay ılım tekniğine dayanan yapay sinir ağı Ziarati and Ucan, January 2001 modeli ile gerçek bir firmanın malzeme tedarik zincirinde geleceğe dönük malzeme talep miktarı tahmin edilebilmiştir. Yapay sinir ağlarının hızlı olması, büyük miktardaki verinin ele alınabilmesi, malzeme akış diagramlarında geleceğe yönelik tahminlerde potensiel bir model olmalarını sağlamaktadır. Bu makale, Ziarati and Ucan, January 2001 makalesinin geliştirilmiş biçimidir. Burada yapay sinir ağ YSA yapısı yerine Genetik Hücresel Yapay Sinir Ağ HYSA modeli konulmuştur. Söz konusu yaklaşım daha az parametre ile kestirim yapabilmekte ve dolayısıyla hızlı değişimli gerçek tedarik zincir problemlerine daha hızlı uyum sağlamaktadır. Önerilen modelin, tedarik zinciri problemlerinde, gerek eğitim sürecinin kısaltılmasında gerekse malzeme istek kestirimde üstün başarım göstermesi beklenmektedir.
Anahtar Kelimeler
Kaynakça
- CHUA, L. O., YANG, L. (1988). "Cellular Neural Networks: Theory", IEEE Trans. Circuit and Systems, V35, pp.1257-1272.
- DAVIS, L., (1991). Handbook of Genetic Algorithms, New York: Van Nostrand Reinhold.
- HOLLAND, J.H. (1975). "Outline for a logical theory of adaptive systems: J. Assoc." Computer, v.3, pp.297-314.
- . (1975). Adaptation in neural and artificial systems, Ann Arbor, MI: University of the Michigan Press
- KOZEK, T., ROSKA, T., CHUA, L.O. (1988). "Genetic Algorithms for CNN template Learning", IEEE Trans. Circuit and Systems, V40, pp.392-402.
- STOCKTON, D.T., QUINN, L. (1993). "Identifying Economic Order Quantities Using Genetic Algorithms" International Journal of Operations and Production Management, v.3, n. 11.
- UÇAN, O. et al. (2001). "Separation of Bouguer anomaly map using cellular neural netvvork", Journal of Applied Geophysics 46, pp. 129-142.
- WANG, Q. (2000, November), împroving the Cost Model Development Process Using Neural Networks, Thesis, De Monfort University.
- ZIARATI, M., UCAN, O.N. (2001, January). "Optimisation of Economic Order Quantity Using Neural Netvvorks Approach", Dogus University Journal Number, No: 3, pp. 128-140.
- ZIARATI, R. (1994, May). "Factories of the Future", Invited paper, EUROTECNET Conference, Germany
- ZIARATI, R., KHATAEE, A. (1994, April). "Integrated Business information System (IBIS) - A Quality Led Approach", Keynote Address. SheMet 94, Belfast University Press, Ulster, UK
DESIGN AND DEVELOPMENT OF MATERIAL AND INFORMATION FLOW FOR SUPPLY CHAINS USING GENETIC CELLULAR NETWORKS
Öz
In a recent paper by authors Ziarati and Ucan, January 2001 a Back Propagation-Artificial Neural Network BP-ANN was adapted for predicting the required car parts quantities in a real and major auto parts supplier chain. It was argued that due to the learning ability of neural networks, their speed and capacity to handle large amount of data, they have a potential for predicting components requirements and establishing associated scheduling throughout a given supply chain system. This paper should be considered a continuation of the first paper as the neural network approach introduced in this paper replaces the BP-ANN by a new method viz., Genetic Cellular Neural Network GCNN . The latter approach requires by far less stability parameters and hence better suited to fast changing scenarios as in real supply chain applications. The model has shown promising outcomes in learning and predicting material demand in a supply chain, with high degree of accuracy.
Anahtar Kelimeler
Kaynakça
- CHUA, L. O., YANG, L. (1988). "Cellular Neural Networks: Theory", IEEE Trans. Circuit and Systems, V35, pp.1257-1272.
- DAVIS, L., (1991). Handbook of Genetic Algorithms, New York: Van Nostrand Reinhold.
- HOLLAND, J.H. (1975). "Outline for a logical theory of adaptive systems: J. Assoc." Computer, v.3, pp.297-314.
- . (1975). Adaptation in neural and artificial systems, Ann Arbor, MI: University of the Michigan Press
- KOZEK, T., ROSKA, T., CHUA, L.O. (1988). "Genetic Algorithms for CNN template Learning", IEEE Trans. Circuit and Systems, V40, pp.392-402.
- STOCKTON, D.T., QUINN, L. (1993). "Identifying Economic Order Quantities Using Genetic Algorithms" International Journal of Operations and Production Management, v.3, n. 11.
- UÇAN, O. et al. (2001). "Separation of Bouguer anomaly map using cellular neural netvvork", Journal of Applied Geophysics 46, pp. 129-142.
- WANG, Q. (2000, November), împroving the Cost Model Development Process Using Neural Networks, Thesis, De Monfort University.
- ZIARATI, M., UCAN, O.N. (2001, January). "Optimisation of Economic Order Quantity Using Neural Netvvorks Approach", Dogus University Journal Number, No: 3, pp. 128-140.
- ZIARATI, R. (1994, May). "Factories of the Future", Invited paper, EUROTECNET Conference, Germany
- ZIARATI, R., KHATAEE, A. (1994, April). "Integrated Business information System (IBIS) - A Quality Led Approach", Keynote Address. SheMet 94, Belfast University Press, Ulster, UK
Ayrıntılar
| Birincil Dil | İngilizce |
|---|---|
| Bölüm | Araştırma Makalesi |
| Yazarlar | |
| Yayımlanma Tarihi | 1 Ocak 2002 |
| Yayımlandığı Sayı | Yıl 2002 Cilt: 3 Sayı: 1 |