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Intraday shelf replenishment decision support for perishable goods
16 references·0 citing·33 second hop
Intraday shelf replenishment decision support for perishable goods (2020)Intraday shelf replenishment decision sup…Retail forecasting: Research and practice (2019)Retail forecasting: Research …The M4 Competition: Results, findings, conclusion and way forward (2018)The M4 Competition: Results, …The Big Data Newsvendor: Practical Insights from Machine Learning (2018)The Big Data Newsvendor: Prac…Statistical and Machine Learning forecasting methods: Concerns and ways forward (2018)Statistical and Machine Learn…Optimal Forecast Reconciliation for Hierarchical and Grouped Time Series Through Trace Minimization (2018)Optimal Forecast Reconciliati…Automatic time series forecasting: the forecast package for R (2017)Automatic time series forecas…Review of inventory systems with deterioration since 2001 (2012)Review of inventory systems w…The newsvendor problem: Review and directions for future research (2010)The newsvendor problem: Revie…An Empirical Comparison of Machine Learning Models for Time Series Forecasting (2010)An Empirical Comparison of Ma…Forecasting with Exponential Smoothing : The State Space Approach (2008)Forecasting with Exponential …Automatic Time Series Forecasting: The forecast Package for R (2008)Automatic Time Series Forecas…Application of machine learning techniques for supply chain demand forecasting (2007)Application of machine learni…Another look at measures of forecast accuracy (2006)Another look at measures of f…Monte Carlo Sampling Methods (2003)Monte Carlo Sampling MethodsThe Sample Average Approximation Method for Stochastic Discrete Optimization (2002)The Sample Average Approximat…Forecasting principles and practiceForecasting principles and pr…Stochastic Approximation Methods for Constrained and Unconstrained Systems (1978)Bayesian Analysis of DSGE Models (2007)Sample Average Approximation Method for Chance Constrained Programming: Theory and Applications (2009)Frameworks and Results in Distributionally Robust Optimization (2022)A stochastic programming approach for supply chain network design under uncertainty (2004)Convex Approximations of Chance Constrained Programs (2006)Lectures on Stochastic Programming: Modeling and Theory (2009)Introduction to Stochastic Programming (2011)Information Distortion in a Supply Chain: The Bullwhip Effect (1997)The Bullwhip Effect In Supply Chains 1 (1997)Information systems in supply chain integration and management (2003)Artificial intelligence in supply chain management: theory and applications (2009)Predictive big data analytics for supply chain demand forecasting: methods, applications, and research opportunities (2020)Artificial intelligence applications in supply chain management (2021)Time Series Analysis: Forecasting and Control (1977)Time Series Analysis: Forecasting and Control (1977)Forecasting methods and applications (1993)A review and comparison of strategies for multi-step ahead time series forecasting based on the NN5 forecasting competition (2012)Machine Learning Strategies for Time Series Forecasting (2013)Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root (1981)Testing the null hypothesis of stationarity against the alternative of a unit root (1992)DeepAR: Probabilistic forecasting with autoregressive recurrent networks (2019)Time Series Analysis Forecasting and Control. (1971)The M4 Competition: 100,000 time series and 61 forecasting methods (2019)Forecasting: theory and practice (2022)Recurrent Neural Networks for Time Series Forecasting: Current status and future directions (2020)A Comparison of ARIMA and LSTM in Forecasting Time Series (2018)The Performance of LSTM and BiLSTM in Forecasting Time Series (2019)The tourism forecasting competition (2010)M5 accuracy competition: Results, findings, and conclusions (2022)A note on the validity of cross-validation for evaluating autoregressive time series prediction (2017)A hybrid method of exponential smoothing and recurrent neural networks for time series forecasting (2019)An optimized model using LSTM network for demand forecasting (2020)
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References

  • 2006Another look at measures of forecast accuracy5,736 cited
  • n.d.Forecasting principles and practice4,364 cited
  • 2008Automatic Time Series Forecasting: The forecast Package for R3,538 cited
  • 2002The Sample Average Approximation Method for Stochastic Discrete Optimization1,989 cited
  • 2018Statistical and Machine Learning forecasting methods: Concerns and ways forward1,515 cited
  • 2017Automatic time series forecasting: the forecast package for R978 cited
  • 2003Monte Carlo Sampling Methods916 cited
  • 2008Forecasting with Exponential Smoothing : The State Space Approach818 cited
  • 2010An Empirical Comparison of Machine Learning Models for Time Series Forecasting793 cited
  • 2007Application of machine learning techniques for supply chain demand forecasting669 cited
  • 2012Review of inventory systems with deterioration since 2001636 cited
  • 2018The M4 Competition: Results, findings, conclusion and way forward634 cited
  • 2018The Big Data Newsvendor: Practical Insights from Machine Learning510 cited
  • 2010The newsvendor problem: Review and directions for future research484 cited
  • 2019Retail forecasting: Research and practice357 cited

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  • 2018Optimal Forecast Reconciliation for Hierarchical and Grouped Time Series Through Trace Minimization332 cited
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