AIOCAug 16, 2024

Magazine Supply Optimization: a Case-study

arXiv:2408.08637v1h-index: 7
Originality Incremental advance
AI Analysis

This addresses supply planning challenges for magazine publishers, though it is incremental as it builds on existing optimization methods with domain-specific adaptations.

The paper tackles magazine supply optimization by introducing AthenIA, a solution that uses a novel group conformalized quantile regression method and optimization techniques to plan supply for over 20,000 points of sale in France, balancing out-of-stock and over-supply costs.

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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes