Using machine learning to include planners' preferences in railway crew scheduling optimization
Year of publication: |
2023
|
---|---|
Authors: | Gattermann-Itschert, Theresa ; Poreschack, Laura Maria ; Thonemann, Ulrich |
Published in: |
Transportation science. - Hanover, Md. : INFORMS, ISSN 1526-5447, ZDB-ID 2015901-8. - Vol. 57.2023, 3, p. 796-812
|
Subject: | crew scheduling | machine learning | optimization | preferences | Künstliche Intelligenz | Artificial intelligence | Personaleinsatzplanung | Crew scheduling | Schienenverkehr | Railway transport | Scheduling-Verfahren | Scheduling problem | Theorie | Theory | Algorithmus | Algorithm |
-
Learning to enumerate shifts for large-scale flexible personnel scheduling problems
Rastgar-Amini, Farin, (2022)
-
A brand-and-price algorithm for a hierarchical crew scheduling problem
Faneyte, Diego B. C., (2001)
-
Two-level decomposition algorithm for crew rostering problems with fair working condition
Nishi, Tatsushi, (2014)
- More ...
-
How training on multiple time slices improves performance in churn prediction
Gattermann-Itschert, Theresa, (2021)
-
Gattermann-Itschert, Theresa, (2022)
-
Thonemann, Ulrich, (2007)
- More ...