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Reinforcement learning framework for freight demand forecasting to support operational planning decisions
15 references·6 citing·48 second hop
Reinforcement learning framework for freight demand forecasting to support operational planning decisions (2020)Reinforcement learning framework for frei…A Multimodal Elastic Trade Coefficients MRIO Model for Freight Demand in Europe (2013)A Multimodal Elastic Trade Co…Forecasting Time Series With Complex Seasonal Patterns Using Exponential Smoothing (2011)Forecasting Time Series With …Application and Validation of Dynamic Freight Simulation–Assignment Model to Large-Scale Intermodal Rail Network (2008)Application and Validation of…Multiple neural networks for a long term time series forecast (2004)Multiple neural networks for …COMBINING FORECASTING PROCEDURES: SOME THEORETICAL RESULTS (2004)COMBINING FORECASTING PROCEDU…Thick modeling (2003)Thick modelingUnmasking the Theta method (2002)Unmasking the Theta methodA reinforcement learning approach to a single leg airline revenue management problem with multiple fare classes and overbooking (2002)A reinforcement learning appr…Reinforcement-based vs. Belief-based Learning Models in Experimental Asymmetric-information Games (2000)Reinforcement-based vs. Belie…INTERMODAL FREIGHT TRANSPORTATION (2000)INTERMODAL FREIGHT TRANSPORTA…Predicting How People Play Games: Reinforcement Learning in Experimental Games with Unique, Mixed Strategy Equilibria (1998)Predicting How People Play Ga…Learning in extensive-form games: Experimental data and simple dynamic models in the intermediate term (1995)Learning in extensive-form ga…Forecasting Transformed Series (1976)Forecasting Transformed SeriesExperience with Forecasting Univariate Time Series and the Combination of Forecasts (1974)Experience with Forecasting U…Forecasting principles and practiceForecasting principles and pr…A systematic review of machine learning approaches in inventory control optimization (2025)A systematic review of machin…Learning-Based Optimisation for Integrated Problems in Intermodal Freight Transport: Preliminaries, Strategies, and State of the Art (2024)Learning-Based Optimisation f…Unlocking the potential of quality as a core marketing strategy in remanufactured circular products: A machine learning enabled multi-theoretical perspective (2023)Unlocking the potential of qu…On the use of machine learning in supply chain management: a systematic review (2023)On the use of machine learnin…Optimizing automotive inbound logistics: A mixed-integer linear programming approach (2022)Optimizing automotive inbound…Forecasting Shanghai Container Freight Index: A Deep-Learning-Based Model Experiment (2022)Forecasting Shanghai Containe…Science and Human Behavior (1953)Prospect theory: An analysis of decision under risk (1988)The Adaptive Decision Maker (1994)Cooperation and Punishment in Public Goods Experiments (2000)ERC: A Theory of Equity, Reciprocity, and Competition (2000)The Stag Hunt and the Evolution of Social Structure (2003)The Combination of Forecasts (1969)Time Series Analysis: Forecasting and Control (1977)Journal of the American Statistical Association (1995)Inference on Predictability of Foreign Exchange Rates via Generalized Spectrum and Nonlinear Time Series Models (2003)Adaptive combination of forecasts with application to wind energy (2008)Oil price increases and the predictability of equity premium (2019)Time Series Analysis, Forecasting and Control. 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(1971)Forecasting monthly riverflow time series (1985)Heterogeneous Information Arrivals and Return Volatility Dynamics: Uncovering the Long-Run in High Frequency Returns (1996)The role of the log transformation in forecasting economic variables (2010)Combining forecasts: A review and annotated bibliography (1989)Discretion versus policy rules in practice (1993)International house prices and macroeconomic fluctuations (2009)Forecast combinations of computational intelligence and linear models for the NN5 time series forecasting competition (2011)Is there an optimal forecast combination? (2013)A Comparison of ARIMA and LSTM in Forecasting Time Series (2018)The Performance of LSTM and BiLSTM in Forecasting Time Series (2019)Recurrent Neural Networks for Time Series Forecasting: Current status and future directions (2020)
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References

  • n.d.Forecasting principles and practice4,364 cited
  • 1998Predicting How People Play Games: Reinforcement Learning in Experimental Games with Unique, Mixed Strategy Equilibria1,794 cited
  • 1995Learning in extensive-form games: Experimental data and simple dynamic models in the intermediate term1,678 cited
  • 2011Forecasting Time Series With Complex Seasonal Patterns Using Exponential Smoothing1,055 cited
  • 1974Experience with Forecasting Univariate Time Series and the Combination of Forecasts849 cited
  • 1976Forecasting Transformed Series297 cited
  • 2004COMBINING FORECASTING PROCEDURES: SOME THEORETICAL RESULTS221 cited
  • 2003Thick modeling187 cited
  • 2000Reinforcement-based vs. Belief-based Learning Models in Experimental Asymmetric-information Games168 cited
  • 2002Unmasking the Theta method165 cited
  • 2002A reinforcement learning approach to a single leg airline revenue management problem with multiple fare classes and overbooking138 cited
  • 2000INTERMODAL FREIGHT TRANSPORTATION86 cited
  • 2004Multiple neural networks for a long term time series forecast72 cited
  • 2008Application and Validation of Dynamic Freight Simulation–Assignment Model to Large-Scale Intermodal Rail Network28 cited
  • 2013

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A Multimodal Elastic Trade Coefficients MRIO Model for Freight Demand in Europe
19 cited

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  • 2023Unlocking the potential of quality as a core marketing strategy in remanufactured circular products: A machine learning enabled multi-theoretical perspective58 cited
  • 2023On the use of machine learning in supply chain management: a systematic review37 cited
  • 2022Forecasting Shanghai Container Freight Index: A Deep-Learning-Based Model Experiment35 cited
  • 2022Optimizing automotive inbound logistics: A mixed-integer linear programming approach26 cited
  • 2025A systematic review of machine learning approaches in inventory control optimization15 cited
  • 2024Learning-Based Optimisation for Integrated Problems in Intermodal Freight Transport: Preliminaries, Strategies, and State of the Art10 cited