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A graph partitioning strategy for solving large-scale crew scheduling problems
Jütte, Silke; Thonemann, Ulrich - In: OR spectrum : quantitative approaches in management 37 (2015) 1, pp. 137-170
Persistent link: https://www.econbiz.de/10010479974
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Optimizing railway crew scheduling at DB Schenker
Jütte, Silke; Albers, Marc; Thonemann, Ulrich; Haase, Knut - In: Interfaces : the INFORMS journal on the practice of … 41 (2011) 2, pp. 109-122
Persistent link: https://www.econbiz.de/10009125014
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Divide-and-price : a decomposition algorithm for solving large railway crew scheduling problems
Jütte, Silke; Thonemann, Ulrich - In: European journal of operational research : EJOR 219 (2012) 2, pp. 214-223
Persistent link: https://www.econbiz.de/10009514361
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Robust tactical crew scheduling under uncertain demand
Rählmann, Christian; Wagener, Felix; Thonemann, Ulrich - In: Transportation science : a journal of the Institute for … 55 (2021) 6, pp. 1392-1410
Persistent link: https://www.econbiz.de/10012796978
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Railway crew scheduling with semi-flexible timetables
Rählmann, Christian; Thonemann, Ulrich - In: OR spectrum : quantitative approaches in management 42 (2020) 4, pp. 835-862
Persistent link: https://www.econbiz.de/10012419332
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Optimizing railway crew schedules with fairness preferences
Jütte, Silke; Müller, Daniel; Thonemann, Ulrich - In: Journal of scheduling 20 (2017) 1, pp. 43-55
Persistent link: https://www.econbiz.de/10011672018
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Using machine learning to include planners' preferences in railway crew scheduling optimization
Gattermann-Itschert, Theresa; Poreschack, Laura Maria; … - In: Transportation science 57 (2023) 3, pp. 796-812
Persistent link: https://www.econbiz.de/10014311123