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iETS : state space model for intermittent demand forecasting
Svetunkov, Ivan; Boylan, John E. - In: International journal of production economics 265 (2023), pp. 1-15
Persistent link: https://www.econbiz.de/10014437626
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Multivariate Modellierung, Prognose und Evaluation sporadischer Nachfragezeitreihen
Nieberle, Ekaterina - 2016 - 1. Auflage
Persistent link: https://www.econbiz.de/10011491497
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A compound-Poisson Bayesian approach for spare parts inventory forecasting
Babai, M. Zied; Chen, Huijing; Syntetos, A. A.; Lengu, D. - In: International journal of production economics 232 (2021), pp. 1-14
Persistent link: https://www.econbiz.de/10012495564
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A new method to forecast intermittent demand in the presence of inventory obsolescence
Babai, M. Z.; Dallery, Y.; Boubaker, Sabri; Kalai, R. - In: International journal of production economics 209 (2019), pp. 30-41
Persistent link: https://www.econbiz.de/10012013059
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Spare parts demand forecasting : a review on bootstrapping methods
Hasni, M.; Aguir, M. S.; Babai, M. Zied; Jemai, Z. - In: International journal of production research 57 (2019) 15/16, pp. 4791-4804
Persistent link: https://www.econbiz.de/10012193501
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A periodic inventory system of intermittent demand items with fixed lifetimes
Balugani, Elia; Lolli, Francesco; Gamberini, Rita; … - In: International journal of production research 57 (2019) 22, pp. 6993-7005
Persistent link: https://www.econbiz.de/10012193812
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Forecasting intermittent demand for inventory management by retailers : a new approach
Tian, Xin; Wang, Haoqing; Erjiang E. - In: Journal of retailing and consumer services 62 (2021), pp. 1-8
Persistent link: https://www.econbiz.de/10012648973
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Effects of correlation on intermittent demand forecasting and stock control
Altay, Nezih; Litteral, Lewis A.; Rudisill, Frank - In: International journal of production economics 135 (2011) 1, pp. 275-283
Persistent link: https://www.econbiz.de/10009389028
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Spare parts management for irregular demand items
Costantino, Francesco; Di Gravio, Giulio; Patriarca, … - In: Omega : the international journal of management science 81 (2018), pp. 57-66
Persistent link: https://www.econbiz.de/10011906862
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Order-up-to-level inventory optimization model using time-series demand forecasting with ensemble deep learning
Seyedan, Mahya; Mafakheri, Fereshteh; Wang, Chun - In: Supply chain analytics 3 (2023), pp. 1-13
volatility, customer demand is generally changing, and ignoring this uncertainty could lead to under or over-estimation of … before the depletion of stocks due to the lead time between the ordering point and delivery. Therefore, to meet demand while … and big data analytics have made it easier to overcome such a challenge. This study aims to predict future demand in the …
Persistent link: https://www.econbiz.de/10014516502