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Timing intermittent demand with time-varying order-up-to levels
16 references·0 citing·29 second hopsampled
Timing intermittent demand with time-varying order-up-to levels (2022)Timing intermittent demand with time-vary…M5 accuracy competition: Results, findings, and conclusions (2022)M5 accuracy competition: Resu…The M5 competition: Background, organization, and implementation (2021)The M5 competition: Backgroun…Single-hidden layer neural networks for forecasting intermittent demand (2016)Single-hidden layer neural ne…Supply chain forecasting: Theory, practice, their gap and the future (2015)Supply chain forecasting: The…Forecasting intermittent inventory demands: simple parametric methods vs. bootstrapping (2015)Forecasting intermittent inve…Intermittent demand forecasts with neural networks (2013)Intermittent demand forecasts…On the demand distributions of spare parts (2011)On the demand distributions o…Intermittent demand: Linking forecasting to inventory obsolescence (2011)Intermittent demand: Linking …Forecasting the intermittent demand for slow-moving inventories: A modelling approach (2011)Forecasting the intermittent …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…The accuracy of intermittent demand estimates (2004)The accuracy of intermittent …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…Forecasting and Stock Control for Intermittent Demands (1972)Forecasting and Stock Control…Forecasting Sales by Exponentially Weighted Moving Averages (1960)Smoothing, Forecasting and Prediction of Discrete Time Series. (1964)Book Review: Time Series Analysis: Forecasting and Control (1977)Principles of Forecasting (2001)Automatic Time Series Forecasting: The forecast Package for R (2008)Inventory management and production planning and scheduling (1999)Supply Chain Management: Strategy, Planning and Operations (2000)Forecasting: theory and practice (2022)Production and inventory management (1983)25 years of time series forecasting (2006)Exponential smoothing: The state of the art—Part II (2006)The accuracy of extrapolation (time series) methods: Results of a forecasting competition (1982)Error measures for generalizing about forecasting methods: Empirical comparisons (1992)Assessing the vulnerability of supply chains using graph theory (2009)Forecasting with artificial neural networks: (1998)Out-of-sample tests of forecasting accuracy: an analysis and review (2000)Another look at measures of forecast accuracy (2006)Predictive big data analytics for supply chain demand forecasting: methods, applications, and research opportunities (2020)On the categorization of demand patterns (2004)Retail forecasting: Research and practice (2019)The M3-Competition: results, conclusions and implications (2000)Forecasting intermittent demand in manufacturing: a comparative evaluation of Croston's method (1994)Forecasting for Items with Intermittent Demand (1996)Information Distortion in a Supply Chain: The Bullwhip Effect (1997)Supply Chain Management: Strategy, Planning, and Operation (2003)Artificial intelligence applications in supply chain management (2021)DeepAR: Probabilistic forecasting with autoregressive recurrent networks (2019)Forecast combinations: An over 50-year review (2022)Forecast evaluation for data scientists: common pitfalls and best practices (2022)
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References

  • 1972Forecasting and Stock Control for Intermittent Demands868 cited
  • 2022M5 accuracy competition: Results, findings, and conclusions669 cited
  • 2004The accuracy of intermittent demand estimates516 cited
  • 2003A new approach to forecasting intermittent demand for service parts inventories422 cited
  • 2001On the bias of intermittent demand estimates392 cited
  • 2015Supply chain forecasting: Theory, practice, their gap and the future372 cited
  • 2011Intermittent demand: Linking forecasting to inventory obsolescence255 cited
  • 2013Intermittent demand forecasts with neural networks231 cited
  • 2007Lumpy demand forecasting using neural networks220 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 study183 cited
  • 2021The M5 competition: Background, organization, and implementation143 cited
  • 2016Single-hidden layer neural networks for forecasting intermittent demand140 cited
  • 2011Forecasting the intermittent demand for slow-moving inventories: A modelling approach133 cited
  • 2015Forecasting intermittent inventory demands: simple parametric methods vs. bootstrapping

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119 cited
  • 2011On the demand distributions of spare parts101 cited
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