A Demand Forecast Model based on Moving Average and Markov Method

References

• Wheelwright, S. C., and Makridakis, S.: Forcasting Methods for Management. John Wiley and Sons, NewYork, 1985.
   Google Scholar
• McClain, J. O., and Thomas, L. J.: Response Variance Tradeoffs in Adaptive Forecasting, Operations Research 21(2), 554–568 (1973).
   Web of Science ®Google Scholar
• Winters, P. R.: Forecasting Sales by Exponentially Weighted Moving Averages, Management Science 6(3), 324–342 (1960).
   Web of Science ®Google Scholar
• Pasternack B A..Optimal pricing and returns policies for perishable commodities, Marketing Science, Vol 4(4), pp166–67, 1985.
   Google Scholar
• Wu J., Quantity flexiblity contracts under Baysian updating, Comput. Oper. Res. 32 (2005) 1267–1288.
   Google Scholar
• Supply Chain Management in Food Chains: Improving Performance by Reducing Uncertainty,” Into Trans Opl Res, vol 5(6) pp 487∼499, 1998.
   Google Scholar
• D. Barnes-Schuster, Y. Bassok, R. Anupindi, Coordination and flexibility in supply contracts with options, Manuf. Serv. Oper. Manage. 4 (2002) 171–207.
   Google Scholar
• H.L. Lee and C. Billington. “Managing Supply Chain Inventory: Pitfall sand Opportunities,” Sloan Management Review, spring, vol 33, pp65–73, 1992.
   Web of Science ®Google Scholar
• Agrawal N., and Smith, S.A. “Estimating negative binomial demand for retail inventoryManagement with unobservable lost sales,” Naval Research Logistics, 43(6): pp 839–861,1996.
   Web of Science ®Google Scholar
• Cachon, G. and Fisher, M. “Supply chain inventory management and the value of shared Information,” Management Science,Vol 46(8):1032–48, 2000
   Web of Science ®Google Scholar
• M. Chen, H.- L. Cheng, M.-C. Chien, On channel coordination through revenue-sharing contracts with price and shelf-space dependent demand, Appl.Math. Model. 35 (2011) 4886–4901.
   Google Scholar
• M. Erkoc, S.D. Wu, Managing high-tech capacity expansion via reservation contracts, Prod. Oper. Manage. 14 (2005) 232–251.
   Google Scholar
• Y. Zhou, D.-H. Li, Coordinating order quantity decisions in the supply chain contract under random demand, Appl. Math. Model. 31 (2007) 1029–1038.
   Google Scholar
• Hammond, H., “Quick Response in the Apparel Industry,” Harvard Business School Note Cambridge, Massachusetts, N9-690-038, 1990
   Google Scholar
• Casals, J., Jerez, M., & Sotoca, S. (2009). Modelling and forecasting time series sampled at different frequencies. Journal of Forecasting, 28, 316–342
   Web of Science ®Google Scholar
• Riedel, S., & Gabrys, B. (2007). Combination of multi level forecasts. Journal of VLSI Signal Processing Systems, 49, 265–280.
   Web of Science ®Google Scholar
• Bermudez, J. D., Segura, J. V., & Vercher, E. (2007). Holt- Winters forecasting: an alternative formulation applied to UK air passenger data. Journal of Applied Statistics, 34, 1075 1090.
   Web of Science ®Google Scholar
• Chu, F.-L. (2009). Forecasting tourism demand with ARMA-based methods. Tourism Management, 30, 740–751.
   Web of Science ®Google Scholar
• Chang, C.-L., Sriboonchitta, S., & Wiboonpongse, A. (2009). Modelling and forecasting tourism from East Asia to Thailand under temporal and spatial aggregation. Mathematics and Computers in Simulation, 79, 1730–1744.
   Web of Science ®Google Scholar
• Gil-Alana, A. L., Cunado, J., & de Gracia, F. P. (2008). Tourism in the Canary Islands: forecasting using several seasonal time series models. Journal of Forecasting, 27, 621–636.
   Web of Science ®Google Scholar
• Billiton, R., and R.N. ALLAN (1996). Reliability evaluation of power systems, New York, Plenum Press,
   Google Scholar
• Athanasopoulos, G., Ahmed, R. A., & Hyndman, R. J. (2009). Hierarchical forecasts for Australian domestic tourism. International Journal of Forecasting, 25, 146–166.
   Web of Science ®Google Scholar
• Zhang SJ, He Y.A Grey–Markov forecasting model for forecasting the total power requirement of agricultural machinery in Shanxi Province. J Shanxi AgricUniv (Nat Sci Edi) 21(3): 299–302, 2001.
   Google Scholar
• DiyarAkay, Mehmet Atak; “Grey prediction with rolling mechanism for electricity demand forecasting ofTurkey”, Energy; 32(9): 1670–1675, 2007.
   Web of Science ®Google Scholar
• Min Huang, Yong He, Haiyan Cen; “Predictive analysis on electric-power supply and demand in China” Renewable Energy; 32(7): 1165–1174, 2007
   Web of Science ®Google Scholar
• Armstrong, J. S. (2001). Principles of forecasting: a handbook for researchers and practitioners. Norwell, MA: Kluwer Academic Publishers.
   Google Scholar
• Bijesh, P. and Dr Jayadas, N. H. (2013) - A generalized algorithm for the demand prediction of a short life cycle product supply chain and its implementation in a baked product. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 1, January - February (2013)
   Google Scholar
• G.E.P Box, G.M. Jenkins and G. Reincel, Time Series Analysis: Forecasting and Control, Prentice Hall, 1994.
   Google Scholar