An algorithm selection approach for the flexible job shop scheduling problem: choosing constraint programming solvers through machine learning

DOI10.1016/j.ejor.2022.01.034OpenAlexW4226210625WikidataQ113875428 ScholiaQ113875428MaRDI QIDQ2672113

Marcus Müller, Dominik Kress, David Müller, Erwin Pesch

Publication date: 8 June 2022

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ejor.2022.01.034

zbMATH Keywords

schedulingmachine learningconstraint programmingalgorithm selectiondeep neural networks

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Deterministic scheduling theory in operations research (90B35)

Uses Software

• CPLEX
• JOBSHOP
• Choco
• MiniZinc
• Gecode
• SATzilla
• WEKA
• darch
• C4.5
• OR-tools
• PyTorch
• ILOG SCHEDULE
• Adam
• GitHub
• CHUFFED
• AClib
• CP Optimizer

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