138 research outputs found
Propagating Conjunctions of AllDifferent Constraints
We study propagation algorithms for the conjunction of two AllDifferent
constraints. Solutions of an AllDifferent constraint can be seen as perfect
matchings on the variable/value bipartite graph. Therefore, we investigate the
problem of finding simultaneous bipartite matchings. We present an extension of
the famous Hall theorem which characterizes when simultaneous bipartite
matchings exists. Unfortunately, finding such matchings is NP-hard in general.
However, we prove a surprising result that finding a simultaneous matching on a
convex bipartite graph takes just polynomial time. Based on this theoretical
result, we provide the first polynomial time bound consistency algorithm for
the conjunction of two AllDifferent constraints. We identify a pathological
problem on which this propagator is exponentially faster compared to existing
propagators. Our experiments show that this new propagator can offer
significant benefits over existing methods.Comment: AAAI 2010, Proceedings of the Twenty-Fourth AAAI Conference on
Artificial Intelligenc
Abscon 112: towards more robustness
dans le cadre de CP'08International audienceThis paper describes the three main improvements made to the solver Abscon 109 [9]. The new version, Abscon 112, is able to automatically break some variable symmetries, infer allDifferent constraints from cliques of variables that are pair-wise irreexive, and use an optimized version of the STR (Simple Tabular Reduction) technique initially introduced by J. Ullmann for table constraints
XCSP3-core: A Format for Representing Constraint Satisfaction/Optimization Problems
In this document, we introduce XCSP3-core, a subset of XCSP3 that allows us
to represent constraint satisfaction/optimization problems. The interest of
XCSP3-core is multiple: (i) focusing on the most popular frameworks (CSP and
COP) and constraints, (ii) facilitating the parsing process by means of
dedicated XCSP3-core parsers written in Java and C++ (using callback
functions), (iii) and defining a core format for comparisons (competitions) of
constraint solvers.Comment: arXiv admin note: substantial text overlap with arXiv:1611.0339
Finite Domain Bounds Consistency Revisited
A widely adopted approach to solving constraint satisfaction problems
combines systematic tree search with constraint propagation for pruning the
search space. Constraint propagation is performed by propagators implementing a
certain notion of consistency. Bounds consistency is the method of choice for
building propagators for arithmetic constraints and several global constraints
in the finite integer domain. However, there has been some confusion in the
definition of bounds consistency. In this paper we clarify the differences and
similarities among the three commonly used notions of bounds consistency.Comment: 12 page
Self-decomposable Global Constraints
International audienceScalability becomes more and more critical to decision support technologies. In order to address this issue in Constraint Programming, we introduce the family of self-decomposable constraints. These constraints can be satisfied by applying their own filtering algorithms on variable subsets only. We introduce a generic framework which dynamically decompose propagation, by filtering over variable subsets. Our experiments over the CUMULATIVE constraint illustrate the practical relevance of self-decomposition
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