Higher-Order Consistencies through GAC on Factor Variables

Likitvivatanavong, Chavalit; Xia, Wei; Yap, Roland H. C.

doi:10.1007/978-3-319-10428-7_37

Cited by 6 publications

(3 citation statements)

References 18 publications

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“…The factor encoding of table constraints [5] may be useful to strengthen propagation when a problem class has overlapping table constraints (or tabulation produces overlapping table constraints). It is enabled with the following flag.…”

Section: Factor Encodingmentioning

confidence: 99%

Savile Row Manual

Nightingale

2022

Preprint

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Section: Factor Encodingmentioning

confidence: 99%

Savile Row Manual

Nightingale

2022

Preprint

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“…The factor encoding (FE) (Likitvivatanavong, Xia, and Yap 2014) and factor decomposition encoding (FDE) (Likitvivatanavong, Xia, and Yap 2015) factor out the commonly shared variables between each pair of constraints, then create new variable for each set of the share variables. In FE, the new variable in the encoding returns back to the constraint where it comes from.…”

Section: Stronger Consistency By Encodingsmentioning

confidence: 99%

Generalized Arc Consistency Algorithms for Table Constraints: A Summary of Algorithmic Ideas

Yap

Xia

Wang

2020

AAAI

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Constraint Programming is a powerful paradigm to model and solve combinatorial problems. While there are many kinds of constraints, the table constraint (also called a CSP) is perhaps the most significant—being the most well-studied and has the ability to encode any other constraints defined on finite variables. Thus, designing efficient filtering algorithms on table constraints has attracted significant research efforts. In turn, there have been great improvements in efficiency over time with the evolution and development of AC and GAC algorithms. In this paper, we survey the existing filtering algorithms for table constraint focusing on historically important ideas and recent successful techniques shown to be effective.

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“…Finally, a simple and efficient way to incorporate strong local consistency reasoning into CP solvers, through the use of a reformulation, was very recently proposed [27]. The main idea of the technique, called factor encoding, is to formulate new variables by extracting commonly shared variables from the constraints' scopes and then to reattach them back to the constraints where they come from.…”

Section: Related Workmentioning

confidence: 99%

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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Higher-Order Consistencies through GAC on Factor Variables

Cited by 6 publications

References 18 publications

Savile Row Manual

Savile Row Manual

Generalized Arc Consistency Algorithms for Table Constraints: A Summary of Algorithmic Ideas

Strong local consistency algorithms for table constraints

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