Magazine Supply Optimization: a Case-study
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Abstract (arXiv)
Supply optimization is a complex and challenging task in the magazine retail industry because of the fixed inventory assumption, irregular sales patterns, and varying product and point-of-sale characteristics. We introduce AthenIA, an industrialized magazine supply optimization solution that plans the supply for over 20,000 points of sale in France. We modularize the supply planning process into a four-step pipeline: demand sensing, optimization, business rules, and operating. The core of the solution is a novel group conformalized quantile regression method that integrates domain expert insights, coupled with a supply optimization technique that balances the costs of out-of-stock against the costs of over-supply. AthenIA has proven to be a valuable tool for magazine publishers, particularly in the context of evolving economic and ecological challenges.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 7 of its 30 references that are in the map. First posted on arXiv 16 Aug 2024.
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References · 7
- 2017DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networkscited by 1,013
- 2021A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantificationcited by 792
- 2019N-BEATS: Neural basis expansion analysis for interpretable time series forecastingcited by 753
- 2020Conformal prediction for time seriescited by 53
- 2017Predicting Station-level Hourly Demands in a Large-scale Bike-sharing Network: A Graph Convolutional Neural Network Approachcited by 35
- 2023Deep Learning based Forecasting: a case study from the online fashion industrycited by 12
- 2021Retail Store Layout Optimization for Maximum Product Visibilitycited by 2
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