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Combining Arc-Consistency and Dual Lagrangean Relaxation for Filtering CSPs

Abstract : This paper presents a CSPs filtering method combining arc-consistency and dual Lagrangean relaxation techniques. First, we model the constraint satisfaction problem as a 0/1 linear integer program (IP); then, the consistency of a value is defined as an optimization problem on which a dual Lagrangean relaxation is defined. While solving the dual Lagrangean relaxation, values inconsistencies may be detected (dual Lagrangean inconsistent values); the constraint propagation of this inconsistency can be performed by arc-consistency. After having made the CSP arc-consistent, the process iteratively selects values of variables which may be dual Lagrangean inconsistent. Computational experiments performed over randomly generated problems show the advantages of the hybrid filtering technique combining arc-consistency and dual Lagrangean relaxation.
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Conference papers
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https://hal.archives-ouvertes.fr/hal-00153285
Contributor : Hachemi Bennaceur <>
Submitted on : Friday, June 8, 2007 - 5:15:20 PM
Last modification on : Tuesday, October 20, 2020 - 12:08:02 PM

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  • HAL Id : hal-00153285, version 1

Citation

Mohand Ou Idir Khemmoudj, Hachemi Bennaceur, Anass Nagih. Combining Arc-Consistency and Dual Lagrangean Relaxation for Filtering CSPs. Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems, 2005, pp.258-272. ⟨hal-00153285⟩

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