Global Constraints: A Survey

Régin, Jean‐Charles

doi:10.1007/978-1-4419-1644-0_3

Cited by 33 publications

(20 citation statements)

References 83 publications

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“…In a constraint programming model, different aspects of the problem can be expressed by so-called global constraints that capture the combinatorial structures forming the problem [47,32]. For example, in the case of the Traveling Salesman Problem with Time Windows, one global constraint may capture the fact that we need to have a closed tour, while another global constraint may capture the time window information.…”

Section: Introductionmentioning

confidence: 99%

Improved filtering for weighted circuit constraints

et al. 2012

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We study the weighted circuit constraint in the context of constraint programming. It appears as a substructure in many practical applications, particularly routing problems. We propose a domain filtering algorithm for the weighted circuit constraint that is based on the 1-tree relaxation of Held and Karp. In addition, we study domain filtering based on an additive bounding procedure that combines the 1-tree relaxation with the assignment problem relaxation. Experimental results on Traveling Salesman Problem instances demonstrate that our filtering algorithms can dramatically reduce the problem size. In particular, the search tree size and solving time can be reduced by several orders of magnitude, compared to existing constraint programming approaches. Moreover, for medium-size problem instances, our method is competitive with the state-of-the-art special-purpose TSP solver Concorde.

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Section: Introductionmentioning

confidence: 99%

Improved filtering for weighted circuit constraints

et al. 2012

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“…In particular, the remarkable development of global constraints [81] will open up great perspectives for the creation of new innovative tools and processes in this area.…”

Section: Perspectivesmentioning

confidence: 99%

Constraint-Based Testing

Gotlieb

2015

Advances in Computers

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“…The input of SAT solvers is a low-level machine-readable format that humans cannot directly use to write real problems; instead people typically use a pre-processor that generates the instances from some other application data. This is in contrast with the high-level approach of CP, whose main strength is global constraints [5,91,111] and where modeling languages such as OPL [108] allow to express problems at a very high level, thereby making their structure more explicit. A consequence is that SAT, like Mixed Integer Linear Programming, is a technology that is good at solving large numbers of small constraints.…”

Section: Problem Solving In Sat and Cpmentioning

confidence: 99%

Connections and Integration with SAT Solvers: A Survey and a Case Study in Computational Biology

Corblin

Bordeaux²,

Fanchon³

et al. 2010

Hybrid Optimization

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Boolean constraints play a fundamental rôle in optimization and constraint satisfaction. The resolution of these constraints has been the subject of intense and successful work during the past decade, and SAT solvers have reached a spectacular maturity. This chapter gives a brief overview of the relevant literature on modern SAT solvers and on the recent efforts to better integrate Boolean reasoning with other constraint satisfaction techniques. As a case study that illustrates the use of SAT and CP, we consider an application in computational biology: the task to build gene regulatory networks (GRNs). We report on experiments made on this problem with a combined SAT/CP approach.F. Corblin ( )

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Global Constraints: A Survey

Cited by 33 publications

References 83 publications

Improved filtering for weighted circuit constraints

Improved filtering for weighted circuit constraints

Constraint-Based Testing

Connections and Integration with SAT Solvers: A Survey and a Case Study in Computational Biology

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