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Forecasting intermittent inventory demands: simple parametric methods vs. bootstrapping
16 references·16 citing·33 second hopsampled
Forecasting intermittent inventory demands: simple parametric methods vs. bootstrapping (2015)Forecasting intermittent inventory demand…Intermittent demand: Linking forecasting to inventory obsolescence (2011)Intermittent demand: Linking …An aggregate–disaggregate intermittent demand approach (ADIDA) to forecasting: an empirical proposition and analysis (2010)An aggregate–disaggregate int…Forecasting intermittent demand: a comparative study (2008)Forecasting intermittent dema…Lumpy demand forecasting using neural networks (2007)Lumpy demand forecasting usin…An inventory control system for spare parts at a refinery: An empirical comparison of different re-order point methods (2007)An inventory control system f…Exponential smoothing: The state of the art—Part II (2006)Exponential smoothing: The st…The accuracy of intermittent demand estimates (2004)The accuracy of intermittent …Forecasting for the ordering and stock-holding of spare parts (2004)Forecasting for the ordering …A new approach to forecasting intermittent demand for service parts inventories (2003)A new approach to forecasting…On the bias of intermittent demand estimates (2001)On the bias of intermittent d…The M3-Competition: results, conclusions and implications (2000)The M3-Competition: results, …Forecasting for Items with Intermittent Demand (1996)Forecasting for Items with In…Forecasting intermittent demand in manufacturing: a comparative evaluation of Croston's method (1994)Forecasting intermittent dema…The accuracy of extrapolation (time series) methods: Results of a forecasting competition (1982)The accuracy of extrapolation…Forecasting and Stock Control for Intermittent Demands (1972)Forecasting and Stock Control…Statistical Forecasting for Inventory Control. (1960)Statistical Forecasting for I…Intermittent demand forecasting for spare parts: A Critical review (2021)Intermittent demand forecasti…Forecasting intermittent demand for inventory management by retailers: A new approach (2021)Forecasting intermittent dema…Demand forecasting in supply chains: a review of aggregation and hierarchical approaches (2021)Demand forecasting in supply …We need to talk about intermittent demand forecasting (2020)We need to talk about intermi…Intermittent demand forecasting for spare parts in the heavy-duty vehicle industry: a support vector machine model (2020)Intermittent demand forecasti…Elucidate structure in intermittent demand series (2020)Elucidate structure in interm…Optimising Forecasting Models for Inventory Planning (2019)Optimising Forecasting Models…Forecasting IT security vulnerabilities – An empirical analysis (2019)Forecasting IT security vulne…Forecasting for remanufacturing: The effects of serialization (2019)Forecasting for remanufacturi…The inventory performance of forecasting methods: Evidence from the M3 competition data (2018)The inventory performance of …A new method to forecast intermittent demand in the presence of inventory obsolescence (2018)A new method to forecast inte…Demand Forecasting for Irregular Demands in Business Aircraft Spare Parts Supply Chains by using Artificial Intelligence (AI) (2017)Demand Forecasting for Irregu…Demand forecasting by temporal aggregation: Using optimal or multiple aggregation levels? (2017)Demand forecasting by tempora…An improved method for forecasting spare parts demand using extreme value theory (2017)An improved method for foreca…Forecasting supply chain sporadic demand with nearest neighbor approaches (2016)Forecasting supply chain spor…Forecasting and uncertainty: A survey (2016)Forecasting and uncertainty: …Time Series Analysis: Forecasting and Control (1977)25 years of time series forecasting (2006)Automatic Time Series Forecasting: The forecast Package for R (2008)DeepAR: Probabilistic forecasting with autoregressive recurrent networks (2019)Production and inventory management (1983)Inventory management and production planning and scheduling (1999)Forecasting and operational research: a review (2008)Retail forecasting: Research and practice (2019)Combining forecasts: A review and annotated bibliography (1989)Statistical and Machine Learning forecasting methods: Concerns and ways forward (2018)Recurrent Neural Networks for Time Series Forecasting: Current status and future directions (2020)Decision Systems for Inventory Management and Production Planning (1979)Evaluation of forecasting methods for intermittent parts demand in the field of aviation: a predictive model (2003)Intermittent demand forecasts with neural networks (2013)Forecasting Sales by Exponentially Weighted Moving Averages (1960)Forecasting seasonals and trends by exponentially weighted moving averages (2004)A hybrid method of exponential smoothing and recurrent neural networks for time series forecasting (2019)Artificial intelligence applications in supply chain management (2021)Forecasting: theory and practice (2022)An overview of recent literature on spare parts inventories (2002)‘Horses for Courses’ in demand forecasting (2014)Single-hidden layer neural networks for forecasting intermittent demand (2016)An Improved Demand Forecasting Model Using Deep Learning Approach and Proposed Decision Integration Strategy for Supply Chain (2019)The Combination of Forecasts (1969)Exponential smoothing: The state of the art (1985)Combining forecasts: A review and annotated bibliography (1990)Error measures for generalizing about forecasting methods: Empirical comparisons (1992)Forecasting methods and applications (1993)The Savings Investment and Valuation of a Corporation (1962)Experience with Forecasting Univariate Time Series and the Combination of Forecasts (1974)ARMA Models and the Box-Jenkins Methodology (1997)A Survey of Forecast Error Measures (2013)Supply chain forecasting: Theory, practice, their gap and the future (2015)
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References

  • 2000The M3-Competition: results, conclusions and implications1,700 cited
  • 1982The accuracy of extrapolation (time series) methods: Results of a forecasting competition1,465 cited
  • 2006Exponential smoothing: The state of the art—Part II953 cited
  • 1960Statistical Forecasting for Inventory Control.831 cited
  • 1972Forecasting and Stock Control for Intermittent Demands761 cited
  • 2004The accuracy of intermittent demand estimates498 cited
  • 2003A new approach to forecasting intermittent demand for service parts inventories395 cited
  • 2001On the bias of intermittent demand estimates363 cited
  • 2011Intermittent demand: Linking forecasting to inventory obsolescence255 cited
  • 1994Forecasting intermittent demand in manufacturing: a comparative evaluation of Croston's method236 cited
  • 2007Lumpy demand forecasting using neural networks220 cited
  • 2004Forecasting for the ordering and stock-holding of spare parts214 cited
  • 1996Forecasting for Items with Intermittent Demand199 cited
  • 2007An inventory control system for spare parts at a refinery: An empirical comparison of different re-order point methods188 cited
  • 2008Forecasting intermittent demand: a comparative study

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183 cited
  • 2010An aggregate–disaggregate intermittent demand approach (ADIDA) to forecasting: an empirical proposition and analysis154 cited
  • Cited by

    • 2019Optimising Forecasting Models for Inventory Planning110 cited
    • 2020We need to talk about intermittent demand forecasting91 cited
    • 2021Intermittent demand forecasting for spare parts: A Critical review89 cited
    • 2021Demand forecasting in supply chains: a review of aggregation and hierarchical approaches87 cited
    • 2017Demand Forecasting for Irregular Demands in Business Aircraft Spare Parts Supply Chains by using Artificial Intelligence (AI)84 cited
    • 2018A new method to forecast intermittent demand in the presence of inventory obsolescence72 cited
    • 2018The inventory performance of forecasting methods: Evidence from the M3 competition data70 cited
    • 2016Forecasting supply chain sporadic demand with nearest neighbor approaches68 cited
    • 2020Intermittent demand forecasting for spare parts in the heavy-duty vehicle industry: a support vector machine model60 cited
    • 2021Forecasting intermittent demand for inventory management by retailers: A new approach58 cited
    • 2017Demand forecasting by temporal aggregation: Using optimal or multiple aggregation levels?54 cited
    • 2020Elucidate structure in intermittent demand series54 cited
    • 2017An improved method for forecasting spare parts demand using extreme value theory50 cited
    • 2019Forecasting IT security vulnerabilities – An empirical analysis50 cited
    • 2016Forecasting and uncertainty: A survey48 cited
    • 2019Forecasting for remanufacturing: The effects of serialization41 cited