Theory of linear and integer programming
Theory of linear and integer programming
Solving Strategies for Highly Symmetric CSPs
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
On the Satisfiability of Symmetrical Constrained Satisfaction Problems
ISMIS '93 Proceedings of the 7th International Symposium on Methodologies for Intelligent Systems
CSPLIB: A Benchmark Library for Constraints
CP '99 Proceedings of the 5th International Conference on Principles and Practice of Constraint Programming
A Constraint Programming Approach to the Stable Marriage Problem
CP '01 Proceedings of the 7th International Conference on Principles and Practice of Constraint Programming
Global Constraints for Lexicographic Orderings
CP '02 Proceedings of the 8th International Conference on Principles and Practice of Constraint Programming
Breaking Row and Column Symmetries in Matrix Models
CP '02 Proceedings of the 8th International Conference on Principles and Practice of Constraint Programming
Integer Linear Programming and Constraint Programming Approaches to a Template Design Problem
INFORMS Journal on Computing
Handbook of Combinatorial Designs, Second Edition (Discrete Mathematics and Its Applications)
Handbook of Combinatorial Designs, Second Edition (Discrete Mathematics and Its Applications)
Function variables for constraint programming: Thesis
AI Communications
Generating effective symmetry-breaking predicates for search problems
Discrete Applied Mathematics
Integer optimization by local search: a domain-independent approach
Integer optimization by local search: a domain-independent approach
Hi-index | 0.00 |
Finite-domain constraint programming has been used with great success to tackle a wide variety of combinatorial problems in industry and academia. To apply finite-domain constraint programming to a problem, it is modelled by a set of constraints on a set of decision variables. A common modelling pattern is the use of matrices of decision variables. The rows and/or columns of these matrices are often symmetric, leading to redundancy in a systematic search for solutions. An effective method of breaking this symmetry is to constrain the assignments of the affected rows and columns to be ordered lexicographically. This paper develops an incremental propagation algorithm, GACLexLeq, that establishes generalised arc consistency on this constraint in O(n) operations, where n is the length of the vectors. Furthermore, this paper shows that decomposing GACLexLeq into primitive constraints available in current finite-domain constraint toolkits reduces the strength or increases the cost of constraint propagation. Also presented are extensions and modifications to the algorithm to handle strict lexicographic ordering, detection of entailment, and vectors of unequal length. Experimental results on a number of domains demonstrate the value of GACLexLeq.