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On Constraint Linear Decompositions Using Mathematical Variables

Abstract : A wide literature exists on constraint programming model linearization, based on integer domain decomposition. This paper considers the systematic study of classical global constraints, but in the context of mathematical variables. We consider constraints originally stated using integer domain variables, for which we investigate new definitions and linear decomposi-tions using bounded rational variables. We introduce a generic scheme for reification and softening. Combined with state-of-the-art decompositions on integer variables, this approach permits solving discrete-continuous high level models using a single modeler, connected to a MILP solver. (BEST PAPER AWARD)
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Submitted on : Wednesday, January 17, 2018 - 3:03:10 PM
Last modification on : Wednesday, January 19, 2022 - 3:48:24 PM
Long-term archiving on: : Saturday, May 5, 2018 - 10:34:21 PM


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Thierry Petit. On Constraint Linear Decompositions Using Mathematical Variables. ICTAI 2017 : IEEE 29th International Conference on Tools with Artificial Intelligence, Nov 2017, Boston, United States. pp.123-130, ⟨10.1109/ICTAI.2017.00030⟩. ⟨hal-01686540⟩



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