A self-learning framework combining association rules and mathematical models to solve production scheduling programs

Data-driven production scheduling and control systems are essential for manufacturing organisations to quickly adjust to the demand for a wide range of bespoke products, often within short lead times. This paper presents a self-learning framework that combines association rules and optimization tech...

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Bibliographic Details
Main Authors: Mateo Del Gallo, Sara Antomarioni, Giovanni Mazzuto, Giulio Marcucci, Filippo Emanuele Ciarapica
Format: Article
Language:English
Published: Taylor & Francis Group 2024-12-01
Series:Production and Manufacturing Research: An Open Access Journal
Subjects:
Online Access:https://www.tandfonline.com/doi/10.1080/21693277.2024.2332285
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