NDLI: Combinatorial and robust optimisation models and algorithms for railway applications

Content Provider	Springer Nature Link
Author	Galli, Laura
Copyright Year	2010
Abstract	The following is a summary of the author’s Ph.D. thesis supervised by Alberto Caprara and Paolo Toth and defended on April 16, 2009 at the Università di Bologna. The thesis is written in English and is available from the author upon request. Railway systems represent a challenging area for operations research, especially when highly-complex and data-intensive applications, such as large-scale transportation networks, are at stake. One of the main issues concerns imperfect information. The classic notion of Robust Optimisation, as a way to represent and handle mathematically systems with not precisely known data, did not prove to be successfully applicable in the railway setting. For this reason a new paradigm has been defined recently in Liebchen et al. (2007): Recoverable robustness. Here we present our research on recoverable robust optimisation models for two important railway problems: Train platforming and Rolling stock planning.
Starting Page	215
Ending Page	218
Page Count	4
File Format	PDF
ISSN	16194500
Journal	4OR
Volume Number	9
Issue Number	2
e-ISSN	16142411
Language	English
Publisher	Springer-Verlag
Publisher Date	2010-08-18
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Mixed integer programming Robust optimisation Train platforming Rolling stock planning Operations Research/Decision Theory Optimization Industrial and Production Engineering
Content Type	Text
Resource Type	Article
Subject	Theoretical Computer Science Management Science and Operations Research Management Information Systems Computational Theory and Mathematics

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