An Efficient Filtering Algorithm for Disjunction of Constraints

Lhomme, Olivier

doi:10.1007/978-3-540-45193-8_76

Cited by 12 publications

(7 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…∨ c k , constructive disjunction propagates constraints c i one by one independently of the others, and finally prunes values that were inconsistent with all c i . This technique has been refined by Lhomme [84]. Bacchus and Walsh proposed a constraint algebra in which we can define meta-constraints as logical expressions composed of simpler constraints [4].…”

mentioning

confidence: 99%

Constraint Propagation

Bessière¹

2006

Foundations of Artificial Intelligence

180

182

View full text Add to dashboard Cite

mentioning

confidence: 99%

Constraint Propagation

Bessière¹

2006

Foundations of Artificial Intelligence

180

182

View full text Add to dashboard Cite

“…Propagating disjunctions is recognised to be an important topic. Many papers have been published in this area (Würtz & Müller, 1996;Lhomme, 2003;Lagerkvist & Schulte, 2009;Jefferson, Moore, Nightingale, & Petrie, 2010). Exploiting strict short supports in the algorithms ShortGAC, HaggisGAC and HaggisGAC-Stable allows us to outperform the traditional Constructive Or algorithm (Würtz & Müller, 1996) by orders of magnitude.…”

Section: Short Supports and Disjunctionmentioning

confidence: 99%

“…In the context of Constructive Or, Lhomme (2003) observed that a support for one disjunct A will support all values of any variable not contained in A. The concept is similar to a short support albeit less general, because the length of the supports is fixed to the length of the disjuncts.…”

Section: Related Workmentioning

confidence: 99%

Short and Long Supports for Constraint Propagation

Nightingale

Gent

Jefferson

et al. 2013

jair

View full text Add to dashboard Cite

Special-purpose constraint propagation algorithms frequently make implicit use of short supports -- by examining a subset of the variables, they can infer support (a justification that a variable-value pair may still form part of an assignment that satisfies the constraint) for all other variables and values and save substantial work -- but short supports have not been studied in their own right. The two main contributions of this paper are the identification of short supports as important for constraint propagation, and the introduction of HaggisGAC, an efficient and effective general purpose propagation algorithm for exploiting short supports. Given the complexity of HaggisGAC, we present it as an optimised version of a simpler algorithm ShortGAC. Although experiments demonstrate the efficiency of ShortGAC compared with other general-purpose propagation algorithms where a compact set of short supports is available, we show theoretically and experimentally that HaggisGAC is even better. We also find that HaggisGAC performs better than GAC-Schema on full-length supports. We also introduce a variant algorithm HaggisGAC-Stable, which is adapted to avoid work on backtracking and in some cases can be faster and have significant reductions in memory use. All the proposed algorithms are excellent for propagating disjunctions of constraints. In all experiments with disjunctions we found our algorithms to be faster than Constructive Or and GAC-Schema by at least an order of magnitude, and up to three orders of magnitude

show abstract

“…A lot of work has been done on dealing with disjunctions of constraints, mostly in the discrete case [6,7] but also in the continuous case [13,4,10]. However, in the latter case, most of the approaches consider a specic subclass on DNCSPs (e.g., [13] cannot handle non-linear equations, [4] considers only convex constraints) or follow a specic algorithmic scheme that cannot easily include the successful constraint programming (CP) techniques developped for NCSPs ( [10] reasons on the logical structure following a SAT approach).…”

Section: Sac'08mentioning

confidence: 99%

“…The extension to disjunctions follows the principle of constructive disjunction [6,7]: a box is consistent with a disjunction if it is the hull of the boxes which are consistent with its alternatives. Example 1.…”

Section: Interval Solving Techniques For Dncspsmentioning

confidence: 99%

Splitting heuristics for disjunctive numerical constraints

Douillard¹,

Jermann²

2008

Proceedings of the 2008 ACM Symposium on Applied Computing

View full text Add to dashboard Cite

Numerical constraint solving techniques operate in a branch& prune fashion, using consistency enforcement techniques to prune the search space and splitting operations to explore it. Extensions address disjunctions of constraints as well, but usually in a restrictive case and not tting well the branch&prune scheme. On the other hand, Ratschan has recently proposed a general framework for rst-order formulas whose atoms are numerical constraints. It extends the notion of consistency to logical terms, but little is done with respect to the splitting operation. In this paper, we explore the potential of splitting heuristics that exploit the logical structure of disjunctive numerical constraint problems in order to simplify the problem along the search. First experiments on CNF formulas show that interesting solving time gains can be achieved by choosing the right splitting points.

show abstract

An Efficient Filtering Algorithm for Disjunction of Constraints

Cited by 12 publications

References 3 publications

Constraint Propagation

Constraint Propagation

Short and Long Supports for Constraint Propagation

Splitting heuristics for disjunctive numerical constraints

Contact Info

Product

Resources

About