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A Hybrid Fuzzy Time Series and Anfıs Approach to Demand Variability In Supply Chain Networks

Year 2009, Volume: 5 Issue: 2, 20 - 34, 01.07.2009

Hakan Tozan Ozalp Vayvay

Abstract

Keywords

-

References

  • Christopher M., Logistic and Supply Chain Management, Pitman Publishing, London, UK, 1994, pp.30.
  • Tozan H, Vayvay O., A Hybrid Grey and ANFIS Approach to BWE in Supply Chain Networks, WSEAS Transactions on Systems, 8, 2009, pp. 461--470.
  • Forrester J., Industrial Dynamics: A Major Breakthrough for Decision Makers, Harvard Business Review, 36, 1958, pp. 37--66.
  • Forrester J., Industrial Dynamics, MIT Press, Cambridge, MA, 1961.
  • Sterman, J. D., Instructions for Running the Beer Distribution Game, System Dynamics Group Working Paper D- 3679, MIT, Sloan School of Management, Cambridge, MA, 1984.
  • Sterman J.D., Modeling Managerial Behavior: Misperception of Feedback in a Dynamic Decision Making Experiment, Management Science, 35, 1989, pp.321-399.
  • Sterman J.D., Deterministic Chaos in an Experimental Economic System, Journal of Economic Behavior and Organization, 12, 1989, pp.1-28.
  • Lee H. L., Padmanabhan V., Whang S., The Bullwhip Effect in Supply Chains, MIT Sloan Management Rev., 38, 1997a, pp. 93-10 2.
  • Lee H. L., Padmanabhan V., Whang S., Information Distortion in a Supply Chain: The bullwhip effect, Management Science, 43, 1997b, pp. 546--558.
  • Lee H. L., Aligning Supply Chain Strategies with Product Uncertainties, California Management Review, 44, 2002, pp. 105-119.
  • Lee H. L., Padmanabhan V., Whang S., Information Distortion in a Supply Chain: The bullwhip effect, Management Science, 50, 2004, pp. 1875--1886.
  • Towill D. R.: System Dynamics Background, Methodology and Applications-Part1: Background and Methodology, IEE Computing & Control Engineering Journal, 4 (5), 1993, pp. 201--208.
  • Towill D. R.: System Dynamics Background, Methodology and Applications-Part 2: Applications, IEE Computing & Control Engineering Journal, 4 (5), 1993, pp. 261--268.
  • Dejonckheere J., Disney S.M., Lambrecht M., Towill D.R., Transfer Function Analysis of Forecasting Included Bullwhip in Supply Chains, Int.J. Production Economics, 78, 2002, pp. 133- 144.
  • Dejonckheere J., Disney S.M., Lambrecht M., Towill D.R., Measuring and Avoiding the Bullwhip Effect: A control theoretic approach, European Journal of Operational Research, 147 2003, pp.567-590.
  • Dejonckheere J., Disney S.M., Lambrecht M., Towill D.R., The Impact of Information Enrichment on the Bullwhip Effect in Supply Chains: A control engineering perspective, European Journal of Operational Research, 153, 2004, pp. 727-750.
  • Chen F., Drezner Z., Ryan J., Simchi-Levi D., Quantifying the bullwhip effect: The impact of forecasting, lead time and information, working paper, Department of IE/MS North Western University, Evanston, IL. And School of IE, Purdue University, Lafayette, IN, (1998).
  • Chen F., Decentralized supply chains subject to information delays, Management Science, 45, 1999, pp. 1076--1090.
  • Chen F., Drezner Z., Ryan J., Simchi-Levi D., Quantifying the bullwhip effect: The impact of forecasting, lead time and information, Management Science, 46, 2000 pp.436--443.
  • Chen F., Samroengraja R., The impact of exponential smoothing forecasts on the bullwhip effect, Naval Research Logistics, 47, 2000, pp. 269--286.
  • Carlsson C., Fullér R., Soft computing and the bullwhip effect, Economics and Complexity, 2 1999, pp. 1--26.
  • Carlsson, C., Fullér, R., Reducing the bullwhip effects by means of intelligent, soft computing methods, In Proceeding of the 34th Hawaii International Conference on System Science, 2001, pp. 1--10.
  • Carlsson, C., Fullér, R., A position paper on the agenda for soft decision analysis, Fuzzy Sets and Systems, 131, 2002, PP. 3--11.
  • Carlsson C., Fedrizzi M, Fullér R., Fuzzy logic in management, Kluwer Academic Publishers, Boston, 2004.
  • Efendigil T., Önüt S., Kahraman C., A decision support system for demand forecasting with artificial neural networks and neuro-fuzzy models: A comprehensive analysis, Expert Systems with Applications, 36, 2008, pp..6697--6707.
  • Jang J-S. R., ANFIS: Adaptive network based fuzzy inference system, IEEE Transactions on Fuzzy Systems, Man and Cybernetics, 23, 1993, pp. 665--685.
  • Maduko, A., Developing and testing a neuro-fuzzy classification system for IOS data in asthmatic children, PhD. Thesis, Texas University, 2007.
  • Kahraman C., Fuzzy Applications in Industrial Engineering, (Studies in Fuzziness and Soft Computing, Vol. 201), Springer Verlag , NJ USA, 2006
  • Song Q., Chissom B. S., Forecasting Enrollments with Fuzzy Time Series, Fuzzy Sets and Systems, 54, 1993, pp. 1--9.
  • Song Q., Chissom B. S., Fuzzy Time Series and Its Models, Fuzzy Sets and Systems, 54, 1993, pp. 269--277.
  • Song Q., Chissom B. S., Forecasting Enrollments with Fuzzy Time Series Part II, Fuzzy Sets and Systems, 62, 1994, pp. 1--8.
  • Wang C.H., Predicting Tourism Demand Using Fuzzy Time Series and Hybrid Grey Theory, Tourism Management, 25, 2004, pp.367--374.
  • Tozan H., Vayvay Ö., Fuzzy and Neuro-Fuzzy Approaches to Whiplash Effect in Supply Chains, Journal of Naval Science and Engineering, 4 , 2008, pp. 27--42.
  • Lee H-S., Chou M-T., Fuzzy Forecasting Based on Fuzzy Time Series, International Journal of Computer Mathematics, 81, 2004, pp. 781--789.
  • Hwang J., Chen S. M., Lee C. H., Handling Forecasting Problems Using Fuzzy Time Series, Fuzzy Sets and Systems, 100, 1998, pp. 217--228.
  • Paik S.K., Analysis of the Causes of Bullwhip Effect in Supply Chain: A Simulation Approach, George Washington University Press, 2003

TEDARİK ZİNCİRİ AĞLARINDA TALEP DEĞİŞKENLİĞİNE MELEZ BİR BULANIK ZAMAN SERİSİ VE ANFIS YAKLAŞIM

Year 2009, Volume: 5 Issue: 2, 20 - 34, 01.07.2009

Hakan Tozan Ozalp Vayvay

Abstract

Tedarik zinciri ağlarında safhalar arasındaki talep bilgisi
değişkenliği ve bu değişkenlikteki artış (Kırbaç Etkisi) zincirin toplam
performansına etki eden birkaç sistem kusurunu tetikler. Bu makalede göreli
orta değişken talep bilgisi altında, tedarik zinciri ağlarındaki talep
değişkenliğinin önerilen bulanık zaman serileri tahmin modeli ve ANFIS
tabanlı karar sürecinden oluşan melez sisteme verdiği tepki, bir benzetim
modeli ile analiz edilmiştir.

Keywords

Tedarik Zinciri Tahmin Kırbaç Etkisi Bulanık Zaman Serileri ANFIS

References

  • Christopher M., Logistic and Supply Chain Management, Pitman Publishing, London, UK, 1994, pp.30.
  • Tozan H, Vayvay O., A Hybrid Grey and ANFIS Approach to BWE in Supply Chain Networks, WSEAS Transactions on Systems, 8, 2009, pp. 461--470.
  • Forrester J., Industrial Dynamics: A Major Breakthrough for Decision Makers, Harvard Business Review, 36, 1958, pp. 37--66.
  • Forrester J., Industrial Dynamics, MIT Press, Cambridge, MA, 1961.
  • Sterman, J. D., Instructions for Running the Beer Distribution Game, System Dynamics Group Working Paper D- 3679, MIT, Sloan School of Management, Cambridge, MA, 1984.
  • Sterman J.D., Modeling Managerial Behavior: Misperception of Feedback in a Dynamic Decision Making Experiment, Management Science, 35, 1989, pp.321-399.
  • Sterman J.D., Deterministic Chaos in an Experimental Economic System, Journal of Economic Behavior and Organization, 12, 1989, pp.1-28.
  • Lee H. L., Padmanabhan V., Whang S., The Bullwhip Effect in Supply Chains, MIT Sloan Management Rev., 38, 1997a, pp. 93-10 2.
  • Lee H. L., Padmanabhan V., Whang S., Information Distortion in a Supply Chain: The bullwhip effect, Management Science, 43, 1997b, pp. 546--558.
  • Lee H. L., Aligning Supply Chain Strategies with Product Uncertainties, California Management Review, 44, 2002, pp. 105-119.
  • Lee H. L., Padmanabhan V., Whang S., Information Distortion in a Supply Chain: The bullwhip effect, Management Science, 50, 2004, pp. 1875--1886.
  • Towill D. R.: System Dynamics Background, Methodology and Applications-Part1: Background and Methodology, IEE Computing & Control Engineering Journal, 4 (5), 1993, pp. 201--208.
  • Towill D. R.: System Dynamics Background, Methodology and Applications-Part 2: Applications, IEE Computing & Control Engineering Journal, 4 (5), 1993, pp. 261--268.
  • Dejonckheere J., Disney S.M., Lambrecht M., Towill D.R., Transfer Function Analysis of Forecasting Included Bullwhip in Supply Chains, Int.J. Production Economics, 78, 2002, pp. 133- 144.
  • Dejonckheere J., Disney S.M., Lambrecht M., Towill D.R., Measuring and Avoiding the Bullwhip Effect: A control theoretic approach, European Journal of Operational Research, 147 2003, pp.567-590.
  • Dejonckheere J., Disney S.M., Lambrecht M., Towill D.R., The Impact of Information Enrichment on the Bullwhip Effect in Supply Chains: A control engineering perspective, European Journal of Operational Research, 153, 2004, pp. 727-750.
  • Chen F., Drezner Z., Ryan J., Simchi-Levi D., Quantifying the bullwhip effect: The impact of forecasting, lead time and information, working paper, Department of IE/MS North Western University, Evanston, IL. And School of IE, Purdue University, Lafayette, IN, (1998).
  • Chen F., Decentralized supply chains subject to information delays, Management Science, 45, 1999, pp. 1076--1090.
  • Chen F., Drezner Z., Ryan J., Simchi-Levi D., Quantifying the bullwhip effect: The impact of forecasting, lead time and information, Management Science, 46, 2000 pp.436--443.
  • Chen F., Samroengraja R., The impact of exponential smoothing forecasts on the bullwhip effect, Naval Research Logistics, 47, 2000, pp. 269--286.
  • Carlsson C., Fullér R., Soft computing and the bullwhip effect, Economics and Complexity, 2 1999, pp. 1--26.
  • Carlsson, C., Fullér, R., Reducing the bullwhip effects by means of intelligent, soft computing methods, In Proceeding of the 34th Hawaii International Conference on System Science, 2001, pp. 1--10.
  • Carlsson, C., Fullér, R., A position paper on the agenda for soft decision analysis, Fuzzy Sets and Systems, 131, 2002, PP. 3--11.
  • Carlsson C., Fedrizzi M, Fullér R., Fuzzy logic in management, Kluwer Academic Publishers, Boston, 2004.
  • Efendigil T., Önüt S., Kahraman C., A decision support system for demand forecasting with artificial neural networks and neuro-fuzzy models: A comprehensive analysis, Expert Systems with Applications, 36, 2008, pp..6697--6707.
  • Jang J-S. R., ANFIS: Adaptive network based fuzzy inference system, IEEE Transactions on Fuzzy Systems, Man and Cybernetics, 23, 1993, pp. 665--685.
  • Maduko, A., Developing and testing a neuro-fuzzy classification system for IOS data in asthmatic children, PhD. Thesis, Texas University, 2007.
  • Kahraman C., Fuzzy Applications in Industrial Engineering, (Studies in Fuzziness and Soft Computing, Vol. 201), Springer Verlag , NJ USA, 2006
  • Song Q., Chissom B. S., Forecasting Enrollments with Fuzzy Time Series, Fuzzy Sets and Systems, 54, 1993, pp. 1--9.
  • Song Q., Chissom B. S., Fuzzy Time Series and Its Models, Fuzzy Sets and Systems, 54, 1993, pp. 269--277.
  • Song Q., Chissom B. S., Forecasting Enrollments with Fuzzy Time Series Part II, Fuzzy Sets and Systems, 62, 1994, pp. 1--8.
  • Wang C.H., Predicting Tourism Demand Using Fuzzy Time Series and Hybrid Grey Theory, Tourism Management, 25, 2004, pp.367--374.
  • Tozan H., Vayvay Ö., Fuzzy and Neuro-Fuzzy Approaches to Whiplash Effect in Supply Chains, Journal of Naval Science and Engineering, 4 , 2008, pp. 27--42.
  • Lee H-S., Chou M-T., Fuzzy Forecasting Based on Fuzzy Time Series, International Journal of Computer Mathematics, 81, 2004, pp. 781--789.
  • Hwang J., Chen S. M., Lee C. H., Handling Forecasting Problems Using Fuzzy Time Series, Fuzzy Sets and Systems, 100, 1998, pp. 217--228.
  • Paik S.K., Analysis of the Causes of Bullwhip Effect in Supply Chain: A Simulation Approach, George Washington University Press, 2003
There are 36 citations in total.

Details

Primary Language Turkish
Journal Section Articles
Authors

Hakan Tozan This is me

Ozalp Vayvay This is me

Publication Date July 1, 2009
Published in Issue Year 2009 Volume: 5 Issue: 2

Cite

APA Tozan, H. ., & Vayvay, O. (2009). TEDARİK ZİNCİRİ AĞLARINDA TALEP DEĞİŞKENLİĞİNE MELEZ BİR BULANIK ZAMAN SERİSİ VE ANFIS YAKLAŞIM. Journal of Naval Sciences and Engineering, 5(2), 20-34.