Till Porrmann
PEVZ-ID
2 Publikationen
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2023 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2984133Römer M, Hagemann F, Porrmann T. Predict, Tune and Optimize for Data-Driven Shift Scheduling with Uncertain Demands. In: Sellmann M, Tierney K, eds. Learning and Intelligent Optimization. 17th International Conference, LION 17, Nice, France, June 4–8, 2023, Revised Selected Papers. Lecture Notes in Computer Science. Cham: Springer International Publishing; 2023: 254-269.PUB | DOI
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2021 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2958571Porrmann T, Römer M. Learning to Reduce State-Expanded Networks for Multi-activity Shift Scheduling. In: Stuckey PJ, ed. Integration of Constraint Programming, Artificial Intelligence, and Operations Research. 18th International Conference, CPAIOR 2021, Vienna, Austria, July 5–8, 2021, Proceedings. Lecture Notes in Computer Science. Vol 12735. Cham: Springer International Publishing; 2021: 383-391.PUB | DOI