INC: a language for incremental computations
PLDI '88 Proceedings of the ACM SIGPLAN 1988 conference on Programming Language design and Implementation
Minimizing conflicts: a heuristic repair method for constraint satisfaction and scheduling problems
Artificial Intelligence - Special volume on constraint-based reasoning
Modern heuristic techniques for combinatorial problems
A filtering algorithm for constraints of difference in CSPs
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Incremental evaluation of computational circuits
SODA '90 Proceedings of the first annual ACM-SIAM symposium on Discrete algorithms
Finite Differencing of Computable Expressions
ACM Transactions on Programming Languages and Systems (TOPLAS)
Using global constraints for local search
DIMACS workshop on on Constraint programming and large scale discrete optimization
A constraint-based architecture for local search
OOPSLA '02 Proceedings of the 17th ACM SIGPLAN conference on Object-oriented programming, systems, languages, and applications
Efficient Local Search with Conflict Minimization: A Case Study of the n-Queens Problem
IEEE Transactions on Knowledge and Data Engineering
Yet Another Local Search Method for Constraint Solving
SAGA '01 Proceedings of the International Symposium on Stochastic Algorithms: Foundations and Applications
CP '02 Proceedings of the 6th International Conference on Principles and Practice of Constraint Programming
Specific Filtering Algorithms for Over-Constrained Problems
CP '01 Proceedings of the 7th International Conference on Principles and Practice of Constraint Programming
Localizer: a Modeling Language for Local Search
INFORMS Journal on Computing
Localizer++: An Open Library for local Search
Localizer++: An Open Library for local Search
Integer optimization by local search: a domain-independent approach
Integer optimization by local search: a domain-independent approach
Generalized arc consistency for global cardinality constraint
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
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In this paper we present a local search constraint solver in which constraints are expressed using cost functions on graph structures of filter constraints of equal type. A similar theoretical approach has previously been used to model a large number of complex global constraints, which motivates the use of such a model in practice. In a local search context, we view global constraints as complex cost functions, encapsulating the structure of the constraints using a graph of variables, values and filter constraints. This representation gives us a declarative model, which can also be used to efficiently compute a cost as well as conflict levels of the variables in the constraints. We have implemented these ideas in a compositional C++ framework called Composer, which can be used to solve systems of graph-based constraints. We demonstrate the usability of this approach on several well-known global constraints, and show by experimental results on two problems that an approach using a graph basis for global constraint modeling is not only possible in practice, but also competitive with existing constraint-based local search systems.