We are thus interested in reducing significant amount of row and column symmetries in matrix models with a polynomial effort. In this respect, we have shown ...

Abstract. Many CSPs can be effectively represented and efficiently solved using matrix models, in which the matrices may have symme-.

Symmetry in a CSP is a permutation of variables, or the values in the domains, or both which preserve the state of the search: either all of them lead to a ...

Abstract. We identify an important class of symmetries in constraint programming: matrices of decision variables with rows and columns that are symmetric.

We discuss different methods of reducing symmetry in CSPs where the variables correspond to the cells of a matrix, and both the rows and the columns of the ...

An algorithm for improving the profile of a sparse symmetric matrix is introduced. Tests on normal equation matrices encountered in adjustments of geodetic ...

We study and generalise symmetry-breaking techniques, such as lexicographic ordering, and propose a labelling technique achieving the same effect. 1 ...

Sep 30, 2019 · Smith, B.M., Gent, I.P.: Reducing symmetry in matrix models: Sbds vs. constraints. In: Proc. of SymCon'01, the CP'01 Workshop on Symmetry in ...

Abstract. We identify an important class of symmetries in constraint programming, arising from matrices of decision variables where rows.

In this paper we address the problem of approximating symmetric systems with systems with the same symmetry.