EconPapers    
Economics at your fingertips  
 

A Flexible, Fast, and Optimal Modeling Approach Applied to Crew Rostering at London Underground

ManMohan Sodhi and Stephen Norris

Annals of Operations Research, 2004, vol. 127, issue 1, 259-281

Abstract: We present a general modeling approach to crew rostering and its application to computer-assisted generation of rotation-based rosters (or rotas) at the London Underground. Our goals were flexibility, speed, and optimality, and our approach is unique in that it achieves all three. Flexibility was important because requirements at the Underground are evolving and because specialized approaches in the literature did not meet our flexibility-implied need to use standard solvers. We decompose crew rostering into stages that can each be solved with a standard commercial MILP solver. Using a 167 MHz Sun UltraSparc 1 and CPLEX 4.0 MILP solver, we obtained high-quality rosters in runtimes ranging from a few seconds to a few minutes within 2% of optimality. Input data were takes from different depots with crew sizes ranging from 30–150 drivers, i.e., with number of duties ranging from about 200–1000. Using an argument based on decomposition and aggregation, we prove the optimality of our approach for the overall crew rostering problem. Copyright Kluwer Academic Publishers 2004

Keywords: crew rostering; rota; mixed-integer linear programming; cyclic graph; decomposition; aggregation (search for similar items in EconPapers)
Date: 2004
References: Add references at CitEc
Citations: View citations in EconPapers (13)

Downloads: (external link)
http://hdl.handle.net/10.1023/B:ANOR.0000019092.76669.a1 (text/html)
Access to full text is restricted to subscribers.

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:annopr:v:127:y:2004:i:1:p:259-281:10.1023/b:anor.0000019092.76669.a1

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10479

DOI: 10.1023/B:ANOR.0000019092.76669.a1

Access Statistics for this article

Annals of Operations Research is currently edited by Endre Boros

More articles in Annals of Operations Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-20
Handle: RePEc:spr:annopr:v:127:y:2004:i:1:p:259-281:10.1023/b:anor.0000019092.76669.a1