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Inventory control with a modified Croston procedure and Erlang distribution

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Cited by:

  1. Cardós, Manuel & Babiloni, Eugenia, 2011. "Exact and approximate calculation of the cycle service level in periodic review inventory policies," International Journal of Production Economics, Elsevier, vol. 131(1), pages 63-68, May.
  2. Teunter, Ruud H. & Syntetos, Aris A. & Zied Babai, M., 2011. "Intermittent demand: Linking forecasting to inventory obsolescence," European Journal of Operational Research, Elsevier, vol. 214(3), pages 606-615, November.
  3. Prestwich, S.D. & Tarim, S.A. & Rossi, R. & Hnich, B., 2014. "Forecasting intermittent demand by hyperbolic-exponential smoothing," International Journal of Forecasting, Elsevier, vol. 30(4), pages 928-933.
  4. Teunter, Ruud & Sani, Babangida, 2009. "On the bias of Croston's forecasting method," European Journal of Operational Research, Elsevier, vol. 194(1), pages 177-183, April.
  5. Leven, Erik & Segerstedt, Anders, 2007. "A scheduling policy for adjusting economic lot quantities to a feasible solution," European Journal of Operational Research, Elsevier, vol. 179(2), pages 414-423, June.
  6. Aiping Jiang & Kwok Leung Tam & Xiaoyun Guo & Yufeng Zhang, 2020. "A new approach to forecasting intermittent demand based on the mixed zero‐truncated Poisson model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(1), pages 69-83, January.
  7. Amniattalab, Ayda & Frenk, J.B.G. & Hekimoğlu, Mustafa, 2023. "On spare parts demand and the installed base concept: A theoretical approach," International Journal of Production Economics, Elsevier, vol. 266(C).
  8. Wallström, Peter & Segerstedt, Anders, 2010. "Evaluation of forecasting error measurements and techniques for intermittent demand," International Journal of Production Economics, Elsevier, vol. 128(2), pages 625-636, December.
  9. Ferbar Tratar, Liljana, 2015. "Forecasting method for noisy demand," International Journal of Production Economics, Elsevier, vol. 161(C), pages 64-73.
  10. Kourentzes, Nikolaos, 2013. "Intermittent demand forecasts with neural networks," International Journal of Production Economics, Elsevier, vol. 143(1), pages 198-206.
  11. Rossetti, Manuel D. & Yasin Ünlü, 2011. "Evaluating the robustness of lead time demand models," International Journal of Production Economics, Elsevier, vol. 134(1), pages 159-176, November.
  12. Tiacci, Lorenzo & Saetta, Stefano, 2009. "An approach to evaluate the impact of interaction between demand forecasting method and stock control policy on the inventory system performances," International Journal of Production Economics, Elsevier, vol. 118(1), pages 63-71, March.
  13. Tiacci, Lorenzo & Saetta, Stefano, 2011. "A heuristic for balancing the inventory level of different locations through lateral shipments," International Journal of Production Economics, Elsevier, vol. 131(1), pages 87-95, May.
  14. Bacchetti, Andrea & Saccani, Nicola, 2012. "Spare parts classification and demand forecasting for stock control: Investigating the gap between research and practice," Omega, Elsevier, vol. 40(6), pages 722-737.
  15. Syntetos, A.A. & Babai, M.Z. & Davies, J. & Stephenson, D., 2010. "Forecasting and stock control: A study in a wholesaling context," International Journal of Production Economics, Elsevier, vol. 127(1), pages 103-111, September.
  16. Gutierrez, Rafael S. & Solis, Adriano O. & Mukhopadhyay, Somnath, 2008. "Lumpy demand forecasting using neural networks," International Journal of Production Economics, Elsevier, vol. 111(2), pages 409-420, February.
  17. Pennings, Clint L.P. & van Dalen, Jan & van der Laan, Erwin A., 2017. "Exploiting elapsed time for managing intermittent demand for spare parts," European Journal of Operational Research, Elsevier, vol. 258(3), pages 958-969.
  18. Anderer, Matthias & Li, Feng, 2022. "Hierarchical forecasting with a top-down alignment of independent-level forecasts," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1405-1414.
  19. Pinçe, Çerağ & Turrini, Laura & Meissner, Joern, 2021. "Intermittent demand forecasting for spare parts: A Critical review," Omega, Elsevier, vol. 105(C).
  20. Sinan Apak, 2015. "A Bayesian Approach Proposal For Inventory Cost and Demand Forecasting," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 3(2), pages 41-48, December.
  21. Kourentzes, Nikolaos, 2014. "On intermittent demand model optimisation and selection," International Journal of Production Economics, Elsevier, vol. 156(C), pages 180-190.
  22. Syntetos, Aris A. & Boylan, John E., 2010. "On the variance of intermittent demand estimates," International Journal of Production Economics, Elsevier, vol. 128(2), pages 546-555, December.
  23. John P. Saldanha & Bradley S. Price & Douglas J. Thomas, 2023. "A nonparametric approach for setting safety stock levels," Production and Operations Management, Production and Operations Management Society, vol. 32(4), pages 1150-1168, April.
  24. Lindsey, Matthew & Pavur, Robert, 2009. "Prediction intervals for future demand of existing products with an observed demand of zero," International Journal of Production Economics, Elsevier, vol. 119(1), pages 75-89, May.
  25. Babai, M. Zied & Ali, Mohammad M. & Nikolopoulos, Konstantinos, 2012. "Impact of temporal aggregation on stock control performance of intermittent demand estimators: Empirical analysis," Omega, Elsevier, vol. 40(6), pages 713-721.
  26. Van der Auweraer, Sarah & Boute, Robert N. & Syntetos, Aris A., 2019. "Forecasting spare part demand with installed base information: A review," International Journal of Forecasting, Elsevier, vol. 35(1), pages 181-196.
  27. Jože Martin Rožanec & Blaž Fortuna & Dunja Mladenić, 2022. "Reframing Demand Forecasting: A Two-Fold Approach for Lumpy and Intermittent Demand," Sustainability, MDPI, vol. 14(15), pages 1-21, July.
  28. Zhou, Chenxi & Viswanathan, S., 2011. "Comparison of a new bootstrapping method with parametric approaches for safety stock determination in service parts inventory systems," International Journal of Production Economics, Elsevier, vol. 133(1), pages 481-485, September.
  29. Teunter, Ruud & Sani, Babangida, 2009. "Calculating order-up-to levels for products with intermittent demand," International Journal of Production Economics, Elsevier, vol. 118(1), pages 82-86, March.
  30. Boylan, J.E. & Syntetos, A.A., 2007. "The accuracy of a Modified Croston procedure," International Journal of Production Economics, Elsevier, vol. 107(2), pages 511-517, June.
  31. Altay, Nezih & Rudisill, Frank & Litteral, Lewis A., 2008. "Adapting Wright's modification of Holt's method to forecasting intermittent demand," International Journal of Production Economics, Elsevier, vol. 111(2), pages 389-408, February.
  32. Li, Chongshou & Lim, Andrew, 2018. "A greedy aggregation–decomposition method for intermittent demand forecasting in fashion retailing," European Journal of Operational Research, Elsevier, vol. 269(3), pages 860-869.
  33. Gardner, Everette Jr., 2006. "Exponential smoothing: The state of the art--Part II," International Journal of Forecasting, Elsevier, vol. 22(4), pages 637-666.
  34. Mekhtiev, Mirza Arif, 2013. "Analytical evaluation of lead-time demand in polytree supply chains with uncertain demand, lead-time and inter-demand time," International Journal of Production Economics, Elsevier, vol. 145(1), pages 304-317.
  35. Tratar, Liljana Ferbar, 2010. "Joint optimisation of demand forecasting and stock control parameters," International Journal of Production Economics, Elsevier, vol. 127(1), pages 173-179, September.
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