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How to effectively use machine learning models to predict the solutions for optimization problems: lessons from loss function
Using machine learning in solving constraint optimization and combinator...
05/14/2021 ∙ by Mahdi Abolghasemi, et al. ∙
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Model selection in reconciling hierarchical time series
Model selection has been proven an effective strategy for improving accu...
10/21/2020 ∙ by Mahdi Abolghasemi, et al. ∙
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Hierarchical forecast reconciliation with machine learning
Hierarchical forecasting methods have been widely used to support aligne...
06/03/2020 ∙ by Evangelos Spiliotis, et al. ∙
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Machine learning applications in time series hierarchical forecasting
Hierarchical forecasting (HF) is needed in many situations in the supply...
12/01/2019 ∙ by Mahdi Abolghasemi, et al. ∙
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Demand forecasting in supply chain: The impact of demand volatility in the presence of promotion
The demand for a particular product or service is typically associated w...
09/28/2019 ∙ by Mahdi Abolghasemi, et al. ∙
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Demand Forecasting in the Presence of Systematic Events: Cases in Capturing Sales Promotions
Reliable demand forecasts are critical for the effective supply chain ma...
09/06/2019 ∙ by Mahdi Abolghasemi, et al. ∙
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