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Global constraints: A survey
 IN
, 2011
"... Constraint programming (CP) is mainly based on filtering algorithms; their association with global constraints is one of the main strengths of CP because they exploit the specific structure of each constraint. This chapter is an overview of these two techniques. A collection of the most frequently u ..."
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Cited by 7 (1 self)
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Constraint programming (CP) is mainly based on filtering algorithms; their association with global constraints is one of the main strengths of CP because they exploit the specific structure of each constraint. This chapter is an overview of these two techniques. A collection of the most frequently used global constraints is given and some filtering algorithms are detailed. In addition, we try to identify how filtering algorithms can be designed. At last, we identify some problems that deserve to be addressed in the future.
Modelling Grammar Constraints with Answer Set Programming
"... Representing and solving constraint satisfaction problems is one of the challenges of artificial intelligence. In this paper, we present answer set programming (ASP) models for an important and very general class of constraints, including all constraints specified via grammars or automata that recog ..."
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Cited by 4 (1 self)
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Representing and solving constraint satisfaction problems is one of the challenges of artificial intelligence. In this paper, we present answer set programming (ASP) models for an important and very general class of constraints, including all constraints specified via grammars or automata that recognise some formal language. We argue that our techniques are effective and efficient, e.g., unitpropagation of an ASP solver can achieve domain consistency on the original constraint. Experiments demonstrate computational impact.
Solving String Constraints: The Case for Constraint Programming
"... Abstract We improve an existing propagator for the contextfree grammar constraint and demonstrate experimentally the practicality of the resulting propagator. The underlying technique could be applied to other existing propagators for this constraint. We argue that constraint programming solvers ar ..."
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Abstract We improve an existing propagator for the contextfree grammar constraint and demonstrate experimentally the practicality of the resulting propagator. The underlying technique could be applied to other existing propagators for this constraint. We argue that constraint programming solvers are more suitable than existing solvers for verification tools that have to solve string constraints, as they have a rich tradition of constraints for membership in formal languages. 1
The weighted GRAMMAR constraint
, 2011
"... We introduce the WEIGHTEDGRAMMAR constraint and propose propagation algorithms based on the CYK parser and the Earley parser. We show that the traces of these algorithms can be encoded as a weighted negation normal form (WNNF), a generalization of NNF that allows nodes to carry weights. Based on thi ..."
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Cited by 2 (0 self)
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We introduce the WEIGHTEDGRAMMAR constraint and propose propagation algorithms based on the CYK parser and the Earley parser. We show that the traces of these algorithms can be encoded as a weighted negation normal form (WNNF), a generalization of NNF that allows nodes to carry weights. Based on this connection, we prove the correctness and complexity of these algorithms. Specifically, these algorithms enforce domain consistency on the WEIGHTEDGRAMMAR constraint in time O(n 3). Further, we propose that the WNNF constraint can be decomposed into a set of primitive arithmetic constraint without hindering propagation.
Explaining Propagators for sDNNF Circuits
"... Abstract. Smooth decomposable negation normal form (sDNNF) circuits are a compact form of representing many Boolean functions, that permit linear time satisfiability checking. Given a constraint defined by an sDNNF circuit, we can create a propagator for the constraint by decomposing the circuit u ..."
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Abstract. Smooth decomposable negation normal form (sDNNF) circuits are a compact form of representing many Boolean functions, that permit linear time satisfiability checking. Given a constraint defined by an sDNNF circuit, we can create a propagator for the constraint by decomposing the circuit using a Tseitin transformation. But this introduces many additional Boolean variables, and hides the structure of the original sDNNF. In this paper we show how we can build a propagator that works on the sDNNF circuit directly, and can be integrated into a lazyclause generationbased constraint solver. We show that the resulting propagator can efficiently solve problems where sDNNF circuits are the natural representation of the constraints of the problem, outperforming the decomposition based approach. 1
Explaining Propagators for Edgevalued Decision Diagrams
, 2013
"... Propagators that combine reasoning about satisfiability and reasoning about the cost of a solution, such as weighted alldifferent, or global cardinality with costs, can be much more effective than reasoning separately about satisfiability and cost. The costmdd constraint is a generic propagator f ..."
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Propagators that combine reasoning about satisfiability and reasoning about the cost of a solution, such as weighted alldifferent, or global cardinality with costs, can be much more effective than reasoning separately about satisfiability and cost. The costmdd constraint is a generic propagator for reasoning about reachability in a multidecision diagram with costs attached to edges (a generalization of costregular). Previous work has demonstrated that adding nogood learning for mdd propagators substantially increases the size and complexity of problems that can be handled by stateoftheart solvers. In this paper we show how to add explanation to the costmdd propagator. We demonstrate on scheduling benchmarks the advantages of a learning costmdd global propagator, over both decompositions of costmdd and mdd with a separate objective constraint using learning.
Domaine: Algorithmique, programmation, logiciels et architectures
, 2011
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DFAbased formulation for constraint negation?
"... Abstract. Global constraint design is a key success of CP for solving hard combinatorial problems. Many works suggest that automatonbased definitions and filtering make easier the design of new global constraints. In this paper, from such a design, we present a preliminary work that gives an autom ..."
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Abstract. Global constraint design is a key success of CP for solving hard combinatorial problems. Many works suggest that automatonbased definitions and filtering make easier the design of new global constraints. In this paper, from such a design, we present a preliminary work that gives an automatonbased definition of the NEGATION of a global constraint. For a given global constraint C, the idea lies in giving operators for computing an automaton that recognizes only tuples that are not solution of C, and use the REGULAR global constraint to automatically reason on this automaton. We implemented this approach for automatonbased global constraints, including global_contiguity and ≤lex constraints, and got experimental results that show that their automatically computed negation is highly competitive with more syntactic transformations. 1
NEGATION for free! ∗
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HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et a ̀ la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. appor t de r ech er ch e
Constraints for Membership in Formal . . .
, 2013
"... This thesis focuses on constraints for membership in formal languages under both the systematic search and stochastic local search approaches to constraint programming (CP). Such constraints are very useful in CP for the following three reasons: They provide a powerful tool for userlevel extensibili ..."
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This thesis focuses on constraints for membership in formal languages under both the systematic search and stochastic local search approaches to constraint programming (CP). Such constraints are very useful in CP for the following three reasons: They provide a powerful tool for userlevel extensibility of CP languages. They are very useful for modelling complex work shift regulation constraints, which exist in many shift scheduling problems. In the analysis, testing, and verification of stringmanipulating programs, string constraints often arise. We show in this thesis that CP solvers with constraints for membership in formal languages are much more suitable than existing solvers used in tools that have to solve string constraints. In the stochastic local search approach to CP, we make the following two contributions: We introduce a stochastic method of maintaining violations for the regular constraint and extend our method to the automaton constraint with counters. To improve the usage of constraints for which there exists no known constanttime algorithm for neighbour evaluation, we introduce a framework of using solution neighbourhoods, and give an efficient algorithm of constructing a solution neighbourhood for the regular constraint. In the systematic search approach to CP, we make the following two contributions: We show that there may be unwanted consequences when using