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. and 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. p. 254-269. Springer International Publishing, Cham (2023).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, P.J. (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. 12735, p. 383-391. Springer International Publishing, Cham (2021).PUB | DOI