Strong Inverse Consistencies for Non-Binary CSPs

Μaragoudakis, Manolis

doi:10.1109/ictai.2007.9

Cited by 9 publications

(9 citation statements)

References 20 publications

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“…proposed, with domain filtering consistencies being especially interesting since they only remove values from domains and thus do not alter the structure of the constraint (hyper)graph or the constraints' relations. Examples of such consistencies for nonbinary constraints include SAC [10], RPWC and maxRPWC [7], and rPIC [33]. Some of the consistencies, are directly defined on both binary and non-binary constraints (i.e., SAC for binary and non-binary constraints).…”

Section: Strong Local Consistencies Several Alternative Local Consistmentioning

confidence: 99%

“…Such methods take advantage of the intersections between constraints in order to identify and remove inconsistent tuples or to add new constraints to the problem (e.g., [35,13]). Quite recently, strong domain filtering consistencies have received attention [7,32]. Moreover, efficient ways to apply relational consistencies were proposed and new consistencies of this type were introduced for binary constraints [19,14,38] and non-binary constraints [16,37].…”

Section: Related Workmentioning

confidence: 99%

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Strong local consistency algorithms for table constraints

Paparrizou¹,

Stergiou²

2015

Constraints

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Table constraints are important in constraint programming as they are present in many real problems from areas such as configuration and databases. As a result, numerous specialized algorithms that achieve generalized arc consistency (GAC) on table constraints have been proposed. Since these algorithms achieve GAC, they operate on one constraint at a time. In this paper we propose new filtering algorithms for positive table constraints that achieve stronger local consistency properties than GAC by exploiting intersections between constraints. The first algorithm, called maxRPWC+, is a domain filtering algorithm that is based on the local consistency maxRPWC and extends the GAC algorithm of Lecoutre and Szymanek [23]. The second algorithm extends the state-of-the-art STR-based algorithms to stronger relation filtering consistencies, i.e., consistencies that can remove tuples from constraints' relations. Experimental results from benchmark problems demonstrate that the proposed algorithms are quite competitive with standard GAC algorithms like STR2 in some classes of problems with intersecting table constraints, being orders of magnitude faster in some cases.

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Section: Strong Local Consistencies Several Alternative Local Consistmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Strong local consistency algorithms for table constraints

Paparrizou¹,

Stergiou²

2015

Constraints

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“…One may apply both PWC and GAC. Pairwise Inverse Consistent (PWIC) [19] iff for each value X a , there is a support for a w.r.t. all constraints involving X, such that the supports in all constraints that overlap on more variables than X have the same values.…”

Section: Strong Local Consistenciesmentioning

confidence: 99%

Integrating Strong Local Consistencies into Constraint Solvers

Vion

Petit²,

Jussien³

2011

Lecture Notes in Computer Science

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Abstract. This article presents a generic scheme for adding strong local consistencies to the set of features of constraint solvers, which is notably applicable to event-based constraint solvers. We encapsulate a subset of constraints into a global constraint. This approach allows a solver to use different levels of consistency for different subsets of constraints in the same model. Moreover, we show how strong consistencies can be applied with different kinds of constraints, including user-defined constraints. We experiment our technique with a coarse-grained algorithm for Max-RPC, called Max-RPC rm , and a variant of it, L-Max-RPC rm . Experiments confirm the interest of strong consistencies for Constraint Programming tools.

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“…One avenue to make solvers more robust is to enforce strong consistencies, i.e., consistencies stronger than GAC. Whereas GAC corresponds to the strongest form of local reasoning when constraints are treated separately, strong consistencies necessarily involve several constraints (e.g., path inverse consistency [12], max-restricted path consistency [8] and their adaptations [20] to non-binary constraints) or even the entire constraint network (e.g., singleton arc consistency [9]). …”

Section: Introductionmentioning

confidence: 99%

A Framework for Decision-Based Consistencies

Condotta

Lecoutre

2011

Principles and Practice of Constraint Programming – CP 2011

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Abstract. Consistencies are properties of constraint networks that can be enforced by appropriate algorithms to reduce the size of the search space to be explored. Recently, many consistencies built upon taking decisions (most often, variable assignments) and stronger than (generalized) arc consistency have been introduced. In this paper, our ambition is to present a clear picture of decision-based consistencies. We identify four general classes (or levels) of decision-based consistencies, denoted by S φ ∆ , E φ ∆ , B φ ∆ and D φ ∆ , study their relationships, and show that known consistencies are particular cases of these classes. Interestingly, this general framework provides us with a better insight into decision-based consistencies, and allows us to derive many new consistencies that can be directly integrated and compared with other ones.

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Strong Inverse Consistencies for Non-Binary CSPs

Abstract: Abstract

Cited by 9 publications

References 20 publications

Strong local consistency algorithms for table constraints

Strong local consistency algorithms for table constraints

Integrating Strong Local Consistencies into Constraint Solvers

A Framework for Decision-Based Consistencies

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