Abstract
Scheduling problems arise from repeatedly selecting one item from a set of candidates based on their states. These problems often reduce to assigning priority scores and choosing the highest-ranked item. In this work, we propose a factorized scheduling principle (FSP) framework to learn interpretable and transferable scheduling rules. The FSP framework represents system states as condition distributions and decomposes a global scheduling principle into additive univariate and pairwise components with identifiability constraints. The scheduling principle enables the framework to maintain a simple priority-based structure during deployment. This principle is learned by using a policy-based objective combined with a temporal-difference signal defined on the condition distribution. Experiments on synthetic and realistic scheduling tasks demonstrate the FSP framework's strong performance, interpretability, and zero-shot generalization across different system scales.
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Publication details
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- Open access
- Green open access
Cite this article
APA 7
Je-Gal, H., & Lee, H. S. (2026). Factorized Scheduling Principle: Learning Interpretable and Transferable Policies via Structured Additive Functions. https://omanscience.com/en/articles/factorized-scheduling-principle-learning-interpretable-and-transferable-policies-via-structured-additive-functions
MLA 9
Je-Gal, Hong, and Hyun-Suk Lee. "Factorized Scheduling Principle: Learning Interpretable and Transferable Policies via Structured Additive Functions." https://omanscience.com/en/articles/factorized-scheduling-principle-learning-interpretable-and-transferable-policies-via-structured-additive-functions.
Chicago (author–date)
Je-Gal, Hong, and Hyun-Suk Lee. 2026. "Factorized Scheduling Principle: Learning Interpretable and Transferable Policies via Structured Additive Functions." https://omanscience.com/en/articles/factorized-scheduling-principle-learning-interpretable-and-transferable-policies-via-structured-additive-functions.
Harvard
Je-Gal, H. and Lee, H. S. (2026) 'Factorized Scheduling Principle: Learning Interpretable and Transferable Policies via Structured Additive Functions', Available at: https://omanscience.com/en/articles/factorized-scheduling-principle-learning-interpretable-and-transferable-policies-via-structured-additive-functions.
Vancouver
Je-Gal H, Lee HS. Factorized Scheduling Principle: Learning Interpretable and Transferable Policies via Structured Additive Functions. https://omanscience.com/en/articles/factorized-scheduling-principle-learning-interpretable-and-transferable-policies-via-structured-additive-functions
IEEE
H. Je-Gal, and H. S. Lee, "Factorized Scheduling Principle: Learning Interpretable and Transferable Policies via Structured Additive Functions," https://omanscience.com/en/articles/factorized-scheduling-principle-learning-interpretable-and-transferable-policies-via-structured-additive-functions.