The presence of symmetry in constraint satisfaction problems can cause a great deal of wasted search effort, and several methods for breaking symmetries have been reported. In this paper we describe a new method called Symmetry Breaking by Nonstationary Optimisation, which interleaves local search in the symmetry group with backtrack search on the constraint problem. It can be tuned to break each symmetry with an arbitrarily high probability with high runtime overhead, or as a lightweight but still powerful method with low runtime overhead. It has negligible memory requirement, it combines well with static lex-leader constraints, and its benefit increases with problem hardness
Symmetry-breaking has been proved to be very effective when combined with complete solvers. Converse...
We introduce the study of Conditional symmetry breaking in constraint programming. This arises in a ...
Symmetries in constraint problems present an opportunity for reducing search. This paper presents L...
The presence of symmetry in constraint satisfaction problems can cause a great deal of wasted search...
We describe a new partial symmetry breaking method that can be used to break arbitrary variable/valu...
We describe a new partial symmetry breaking method that can be used to break arbitrary variable/valu...
We describe a new partial symmetry breaking method that can be used to break arbitrary variable/valu...
Constraint Satisfaction Problems (CSPs) are often highly symmetric. Symmetries can give rise to redu...
Constraint Satisfaction Problems (CSPs) are often highly symmetric. Symmetries can give rise to redu...
Constraint Satisfaction Problems (CSPs) are often highly symmetric. Symmetries can give rise to redu...
Symmetry breaking has been shown to be an important method to speed up the search in constraint sa...
Constraint satisfaction and optimisation problems occur frequently in industry and are usually compu...
Symmetry-breaking has been proved to be very effective when combined with complete solvers. Converse...
Symmetry-breaking has been proved to be very effective when combined with complete solvers. Converse...
In recent years, symmetry breaking for constraint satisfaction problems (CSPs) has attracted con...
Symmetry-breaking has been proved to be very effective when combined with complete solvers. Converse...
We introduce the study of Conditional symmetry breaking in constraint programming. This arises in a ...
Symmetries in constraint problems present an opportunity for reducing search. This paper presents L...
The presence of symmetry in constraint satisfaction problems can cause a great deal of wasted search...
We describe a new partial symmetry breaking method that can be used to break arbitrary variable/valu...
We describe a new partial symmetry breaking method that can be used to break arbitrary variable/valu...
We describe a new partial symmetry breaking method that can be used to break arbitrary variable/valu...
Constraint Satisfaction Problems (CSPs) are often highly symmetric. Symmetries can give rise to redu...
Constraint Satisfaction Problems (CSPs) are often highly symmetric. Symmetries can give rise to redu...
Constraint Satisfaction Problems (CSPs) are often highly symmetric. Symmetries can give rise to redu...
Symmetry breaking has been shown to be an important method to speed up the search in constraint sa...
Constraint satisfaction and optimisation problems occur frequently in industry and are usually compu...
Symmetry-breaking has been proved to be very effective when combined with complete solvers. Converse...
Symmetry-breaking has been proved to be very effective when combined with complete solvers. Converse...
In recent years, symmetry breaking for constraint satisfaction problems (CSPs) has attracted con...
Symmetry-breaking has been proved to be very effective when combined with complete solvers. Converse...
We introduce the study of Conditional symmetry breaking in constraint programming. This arises in a ...
Symmetries in constraint problems present an opportunity for reducing search. This paper presents L...