Constraint Propagation

Bessière, Christian

doi:10.1016/s1574-6526(06)80007-6

Cited by 178 publications

(202 citation statements)

References 79 publications

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“…Recent experiments have been carried out with up to 12 processors [19], and speedups tend somehow to A CSP is defined as a triple .X , D, C /, where X is a set of variables, D is a set of domains, that is, finite sets of possible values (one domain for each variable), and C is a set of constraints restricting the values that the variables can simultaneously take. Classical CSPs usually consider finite domains for the variables (integers or naturals) and solvers based on arc-consistency techniques originating from artificial intelligence research carried out in the 1970s and now generalized under the term of propagation-based methods [23,24]. Such solvers keep an internal representation of variable domains in order to handle all types of constraints.…”

Section: Parallel Local Searchmentioning

confidence: 99%

Targeting the Cell Broadband Engine for constraint‐based local search

Díaz

Abreu

Codognet

2011

Concurrency and Computation

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SUMMARYWe investigated the use of the Cell Broadband Engine (Cell/BE) for constraint-based local search and combinatorial optimization applications. We presented a parallel version of a constraint-based local search algorithm that was chosen because it fits very well the Cell/BE architecture because it requires neither shared memory nor communication among processors. The performance study on several large optimization benchmarks shows mostly linear time speedups, sometimes even super linear. These experiments were carried out on a dual-Cell IBM (Armonk, NY, USA) blade with 16 processors. Besides getting speedups, the execution times exhibit a much smaller variance that benefits applications where a timely reply is critical. Copyright

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Section: Parallel Local Searchmentioning

confidence: 99%

Targeting the Cell Broadband Engine for constraint‐based local search

Díaz

Abreu

Codognet

2011

Concurrency and Computation

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“…The notion of consistency characterizes propagator effectiveness. In this paper, we consider bound (Z)-consistency [3]. When domains are exclusively represented by their bounds (i.e., have no holes), bound (Z)-consistency ensures that for each variable x, x and x can be part of a solution of the constraint.…”

Section: Constraint Programming (Cp)mentioning

confidence: 99%

A Global Constraint for a Tractable Class of Temporal Optimization Problems

Derrien

Fages²,

Petit

et al. 2015

Lecture Notes in Computer Science

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Abstract. This paper is originally motivated by an application where the objective is to generate a video summary, built using intervals extracted from a video source. In this application, the constraints used to select the relevant pieces of intervals are based on Allen's algebra. The best state-of-the-art results are obtained with a small set of ad hoc solution techniques, each specific to one combination of the 13 Allen's relations. Such techniques require some expertise in Constraint Programming. This is a critical issue for video specialists. In this paper, we design a generic constraint, dedicated to a class of temporal problems that covers this case study, among others. ExistAllen takes as arguments a vector of tasks, a set of disjoint intervals and any of the 2 13 combinations of Allen's relations. ExistAllen holds if and only if the tasks are ordered according to their indexes and for any task at least one relation is satisfied, between the task and at least one interval. We design a propagator that achieves bound-consistency in O(n + m), where n is the number of tasks and m the number of intervals. This propagator is suited to any combination of Allen's relations, without any specific tuning. Therefore, using our framework does not require a strong expertise in Constraint Programming. The experiments, performed on real data, confirm the relevance of our approach.

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“…We assume now that, for each activity a ∈ A, the solver maintains Bounds-Consistency [4] (BC) on the constraint s a + p a = e a , independently from our propagator. A special case of FlexC(A, C, K) is the case where all values in K are equal to 0.…”

Section: Definition 2 (K-compulsory Part) Let a ∈ A Be An Activity Amentioning

confidence: 99%