Abstract
In this paper we propose a modification to the standard forecasting, periodic order-up-to-level inventory control approach to dealing with intermittent demand items, when the lead-time length is shorter than the average inter-demand interval. In particular, we develop an approach that relies upon the employment of separate estimates of the inter-demand intervals and demand sizes, when demand occurs, directly for stock control purposes rather than first estimating mean demand and then feeding the results in the stock control procedure. The empirical performance of our approach is assessed by means of analysis on a large demand data set from the Royal Air Force (RAF, UK). Our work allows insights to be gained on the interactions between forecasting and stock control as well as on demand categorization-related issues for forecasting and inventory management purposes.
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References
Altay N, Rudisill F and Litteral LA (2007). Adapting Wright's modification of Holt's method to forecasting intermittent demand. Int J Prod Econ 111: 389–408.
Boylan JE and Syntetos AA (2003). Intermittent demand forecasting: Size-interval methods based on averaging and smoothing. Proceedings of the International Conference Quantitative Methods in Industry and Commerce, Athens.
Boylan JE and Syntetos AA (2006). Accuracy and accuracy-implication metrics for intermittent demand. Foresight: the Int J Appl Forecast 4: 39–42.
Boylan JE, Syntetos AA and Karakostas GC (2008). Classification for forecasting and stock control: a case study. J Opl Res Soc 59: 473–481.
Brown RG (1982). Advanced Service Parts Inventory Control, 2nd ed. Materials Management Systems, Inc: Norwich, Vermont.
Croston JD (1972). Forecasting and stock control for intermittent demands. Opl Res Q 23: 289–304.
Eaves AHC and Kingsman BG (2004). Forecasting for the ordering and stock-holding of spare parts. J Opl Res Soc 55: 431–437.
Eppen GD and Martin RK (1988). An empirical evaluation of constant and adaptive computer forecasting models for inventory control. Decis Sci 8: 228–238.
Fildes R, Crone S, Nikolopoulos K and Syntetos AA (2008). Forecasting and operational research: a review. J Opl Res Soc, in press.
Gardner ES (1990). Evaluating forecast performance in an inventory control system. Mngt Sci 36: 490–499.
Ghobbar AA and Friend J (2002). Sources of intermittent demand for aircraft spare parts within airline operations. J Air Trans Mngt 8: 222–231.
Ghobbar AA and Friend J (2003). Evaluation of forecasting methods for intermittent parts demand in the field of aviation: A predictive model. Comput Opns Res 30: 2097–2114.
Gutierrez RS, Solis AO, Mukhopadhyay S (2008). Lumpy demand forecasting using neural networks. Int J Prod Econ 111: 409–420.
Johnston FR and Boylan JE (1996). Forecasting for items with intermittent demand. J Opl Res Soc 47: 113–121.
Johnston FR, Boylan JE and Shale EA (2003). An examination of the size of orders from customers, their characterisation and the implications for inventory control of slow moving items. J Opl Res Soc 54: 833–837.
Kwan HW (1991). On the demand distributions of slow moving items. Unpublished PhD Thesis, Lancaster University, UK.
Levén E and Segerstedt A (2004). Inventory control with a modified Croston procedure and Erlang distribution. Int J Prod Econ 90: 361–367.
Mahmoud E and Pegels CC (1989). An approach for selecting time series forecasting models. Int J Opns Prod Mngt 10: 50–60.
Sani B and Kingsman BG (1997). Selecting the best periodic inventory control and demand forecasting methods for low demand items. J Opl Res Soc 48: 700–713.
Schultz CR (1987). Forecasting and inventory control for sporadic demand under periodic review. J Opl Res Soc 38: 453–458.
Segerstedt A (1994). Inventory control with variation in lead times, especially when demand is intermittent. lnt J Prod Econ 35: 365–372.
Shale EA, Boylan JE and Johnston FR (2006). Forecasting for intermittent demand: the estimation of an unbiased average. J Opl Res Soc 57: 588–592.
Silver EA (1970). Some ideas related to the inventory control of items having erratic demand patterns. Canadian Opl Res Soc J 8: 87–100.
Strijbosch LWG, Moors JJA and De Kok AG (1997). On the Interaction between Forecasting and Inventory Control. Research memorandum FEW 742, Faculty of Economics and Business Administration, Tilburg University, The Netherlands.
Syntetos AA and Boylan JE (2001). On the bias of intermittent demand estimates. Int J Prod Econ 71: 457–466.
Syntetos AA and Boylan JE (2005). The accuracy of intermittent demand estimates. Int J Forecast 21: 303–314.
Syntetos AA and Boylan JE (2006). On the stock-control performance of intermittent demand estimators. Int J Prod Econ 103: 36–47.
Syntetos AA, Boylan JE and Croston JD (2005). On the categorisation of demand patterns. J Opl Res Soc 56: 495–503.
Syntetos AA, Nikolopoulos K, Boylan JE, Fildes R, Goodwin P (2008). Integrating management judgement into intermittent demand forecasts. Int J Prod Econ, in press.
Ward JB (1978). Determining reorder points when demand is lumpy. Mngt Sci 24: 623–632.
Watson RB (1987). The effects of demand–forecast fluctuations on customer service and inventory cost when demand is lumpy. J Opl Res Soc 38: 75–82.
Willemain TR, Smart CN, Shockor JH and DeSautels PA (1994). Forecasting intermittent demand in manufacturing: A comparative evaluation of Croston's method. Int J Forecast 10: 529–538.
Willams TM (1984). Stock control with sporadic and slow-moving demand. J Opl Res Soc 35: 939–948.
Acknowledgements
The research described in this paper has been supported by the Engineering and Physical Sciences Research Council (EPSRC, UK) grant no. EP/D062942/1. More information on this project may be obtained at: http://www.mams.salford.ac.uk/CORAS/Projects/Forecasting/. Moreover, we would like to acknowledge the constructive comments received by Dr Zied Jemai (Ecole Centrale Paris) and Professor John E. Boylan (Buckinghamshire New University).
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Syntetos, A., Babai, M., Dallery, Y. et al. Periodic control of intermittent demand items: theory and empirical analysis. J Oper Res Soc 60, 611–618 (2009). https://doi.org/10.1057/palgrave.jors.2602593
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DOI: https://doi.org/10.1057/palgrave.jors.2602593