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Strong Bounds Consistencies and Their Application to Linear Constraints

Christian Bessière 1 Anastasia Paparrizou 1 Kostas Stergiou 2
1 COCONUT - Agents, Apprentissage, Contraintes
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : We propose two local consistencies that extend bounds consistency (BC) by simultaneously considering com- binations of constraints as opposed to single constraints. We prove that these two local consistencies are both stronger than BC, but are NP-hard to enforce even when constraints are linear. Hence, we propose two polynomial-time techniques to enforce approximations of these two consistencies on linear constraints. One is a reformulation of the constraints on which we enforce BC whereas the other is a polynomial time algorithm. Both achieve stronger pruning than BC. Our experi- ments show large differences in favor of our approaches.
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Submitted on : Thursday, February 18, 2016 - 9:13:55 PM
Last modification on : Monday, January 11, 2021 - 5:24:08 PM
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  • HAL Id : lirmm-01276177, version 1



Christian Bessière, Anastasia Paparrizou, Kostas Stergiou. Strong Bounds Consistencies and Their Application to Linear Constraints. AAAI Conference on Artificial Intelligence, Jan 2015, Austin, TX, United States. pp.3717-3724. ⟨lirmm-01276177⟩



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