Volume 40, Number 4, October-December 2006Journées Francophones de Programmation par Contraintes 2005
|Page(s)||355 - 379|
|Published online||14 February 2007|
Large neighborhood improvements for solving car sequencing problems
Laboratoire d'Informatique Fondamentale – CNRS UMR 6166, Université de la Méditerranée –
Aix-Marseille II, Parc Scientifique et Technologique de Luminy, case 901, 163 avenue de Luminy, 13288 Marseille Cedex
9, France; email@example.com
2 EXPERIAN-PROLOGIA, Parc Scientifique et Technologique de Luminy, case 919, bâtiment CCIMP, 13288 Marseille Cedex 9, France; firstname.lastname@example.org
Accepted: 20 November 2006
The NP-hard problem of car sequencing has received a lot of attention these last years. Whereas a direct approach based on integer programming or constraint programming is generally fruitless when the number of vehicles to sequence exceeds the hundred, several heuristics have shown their efficiency. In this paper, very large-scale neighborhood improvement techniques based on integer programming and linear assignment are presented for solving car sequencing problems. The effectiveness of this approach is demonstrated through an experimental study made on seminal CSPlib's benchmarks.
Mathematics Subject Classification: 90C27 / 90B35 / 90C10
Key words: Combinatorial optimization / car sequencing/scheduling / very large-scale neighborhood search / integer programming / assignment.
© EDP Sciences, 2007
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.