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OR spectrum : quantitative approaches in management
2
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ECONIS (ZBW)
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1
Optimal dynamic order scheduling under capacity constraints given demand-forecast evolution
Biçer, Işık
;
Seifert, Ralf W.
- In:
Production and operations management : an international …
26
(
2017
)
12
,
pp. 2266-2286
Persistent link: https://www.econbiz.de/10011801514
Saved in:
2
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
Saved in:
3
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
Saved in:
4
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
Saved in:
5
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
Saved in:
6
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
Saved in:
7
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
Saved in:
8
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
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