Large neighborhood improvements for solving car sequencing problems

Bertrand Estellon; Frédéric Gardi; Karim Nouioua

RAIRO - Operations Research (2007)

  • Volume: 40, Issue: 4, page 355-379
  • ISSN: 0399-0559

Abstract

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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.

How to cite

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Estellon, Bertrand, Gardi, Frédéric, and Nouioua, Karim. "Large neighborhood improvements for solving car sequencing problems ." RAIRO - Operations Research 40.4 (2007): 355-379. <http://eudml.org/doc/105354>.

@article{Estellon2007,
abstract = { 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. },
author = {Estellon, Bertrand, Gardi, Frédéric, Nouioua, Karim},
journal = {RAIRO - Operations Research},
keywords = {Combinatorial optimization; car sequencing/scheduling; very large-scale neighborhood search; integer programming; assignment.; assignment},
language = {eng},
month = {2},
number = {4},
pages = {355-379},
publisher = {EDP Sciences},
title = {Large neighborhood improvements for solving car sequencing problems },
url = {http://eudml.org/doc/105354},
volume = {40},
year = {2007},
}

TY - JOUR
AU - Estellon, Bertrand
AU - Gardi, Frédéric
AU - Nouioua, Karim
TI - Large neighborhood improvements for solving car sequencing problems
JO - RAIRO - Operations Research
DA - 2007/2//
PB - EDP Sciences
VL - 40
IS - 4
SP - 355
EP - 379
AB - 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.
LA - eng
KW - Combinatorial optimization; car sequencing/scheduling; very large-scale neighborhood search; integer programming; assignment.; assignment
UR - http://eudml.org/doc/105354
ER -

References

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