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  • [2]
    2023 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2984133
    Römer, Michael, Hagemann, Felix, and Porrmann, Till. “Predict, Tune and Optimize for Data-Driven Shift Scheduling with Uncertain Demands”. Learning and Intelligent Optimization. 17th International Conference, LION 17, Nice, France, June 4–8, 2023, Revised Selected Papers. Ed. Meinolf Sellmann and Kevin Tierney. Cham: Springer International Publishing, 2023. Lecture Notes in Computer Science. 254-269.
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  • [1]
    2021 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2958571
    Porrmann, Till, and Römer, Michael. “Learning to Reduce State-Expanded Networks for Multi-activity Shift Scheduling”. Integration of Constraint Programming, Artificial Intelligence, and Operations Research. 18th International Conference, CPAIOR 2021, Vienna, Austria, July 5–8, 2021, Proceedings. Ed. Peter J. Stuckey. Cham: Springer International Publishing, 2021.Vol. 12735. Lecture Notes in Computer Science. 383-391.
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