Issue |
RAIRO-Oper. Res.
Volume 40, Number 2, April-June 2006
ROADEF 03
|
|
---|---|---|
Page(s) | 77 - 95 | |
DOI | https://doi.org/10.1051/ro:2006018 | |
Published online | 12 October 2006 |
Combining constraint Propagation and meta-heuristics for searching a Maximum Weight Hamiltonian Chain
Bouygues e-Lab, 1 avenue Eugène Freyssinet,
78061 St-Quentin en Yvelines Cedex, France;
e-mail: ycs@caseau.com
Received:
31
December
2005
This paper presents the approach that we developed to solve the ROADEF 2003 challenge problem. This work is part of a research program whose aim is to study the benefits and the computer-aided generation of hybrid solutions that mix constraint programming and meta-heuristics, such as large neighborhood search (LNS). This paper focuses on three contributions that were obtained during this project: an improved method for propagating Hamiltonian chain constraints, a fresh look at limited discrepancy search and the introduction of randomization and de-randomization within our combination algebra. This algebra is made of terms that represent optimization algorithms, following the approach of SALSA [1], which can be generated or tuned automatically using a learning meta-strategy [2]. In this paper, the hybrid combination that is investigated mixes constraint propagation, a special form of limited discrepancy search and large neighborhood search.
© EDP Sciences, 2006
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