EconPapers    
Economics at your fingertips  
 

Robust Train Timetabling

Valentina Cacchiani () and Paolo Toth ()
Additional contact information
Valentina Cacchiani: DEI, University of Bologna
Paolo Toth: DEI, University of Bologna

Chapter Chapter 5 in Handbook of Optimization in the Railway Industry, 2018, pp 93-115 from Springer

Abstract: Abstract Nowadays railway systems are highly affected by disturbances, occurring in daily operations, and causing train delays and passenger inconvenience. Not only they negatively affect the passengers satisfaction, but they also cause additional operational costs, since the planned schedule needs to be modified in real-time. Train timetabling is a particularly critical phase in railway system management, since, in real-time operations, all the changes applied to the planned timetable impact on platform assignment, rolling stock circulation and crew scheduling. Therefore, in the strategic planning, it is an important issue to determine robust timetables, i.e., timetables that “perform well” under disturbances, avoiding delay propagation as much as possible. In this chapter, we present state-of-the-art methods that achieve robust timetables, and discuss their advantages and drawbacks.

Keywords: Rolling Stock Circulation; Light Robustness; Recoverable Robustness; Cacchiani; Strict Robustness (search for similar items in EconPapers)
Date: 2018
References: Add references at CitEc
Citations: View citations in EconPapers (6)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:isochp:978-3-319-72153-8_5

Ordering information: This item can be ordered from
http://www.springer.com/9783319721538

DOI: 10.1007/978-3-319-72153-8_5

Access Statistics for this chapter

More chapters in International Series in Operations Research & Management Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-04-01
Handle: RePEc:spr:isochp:978-3-319-72153-8_5