TY - JOUR
T1 - Properties of a representation of a basis for the null space
AU - Gill, Philip E.
AU - Murray, Walter
AU - Saunders, Michael A.
AU - Stewart, G. W.
AU - Wright, Margaret H.
PY - 1985/11
Y1 - 1985/11
N2 - Given a rectangular matrix A(x) that depends on the independent variables x, many constrained optimization methods involve computations with Z(x), a matrix whose columns form a basis for the null space of AT(x). When A is evaluated at a given point, it is well known that a suitable Z (satisfying ATZ = 0) can be obtained from standard matrix factorizations. However, Coleman and Sorensen have recently shown that standard orthogonal factorization methods may produce orthogonal bases that do not vary continuously with x; they also suggest several techniques for adapting these schemes so as to ensure continuity of Z in the neighborhood of a given point. This paper is an extension of an earlier note that defines the procedure for computing Z. Here, we first describe how Z can be obtained by updating an explicit QR factorization with Householder transformations. The properties of this representation of Z with respect to perturbations in A are discussed, including explicit bounds on the change in Z. We then introduce regularized Householder transformations, and show that their use implies continuity of the full matrix Q. The convergence of Z and Q under appropriate assumptions is then proved. Finally, we indicate why the chosen form of Z is convenient in certain methods for nonlinearly constrained optimization.
AB - Given a rectangular matrix A(x) that depends on the independent variables x, many constrained optimization methods involve computations with Z(x), a matrix whose columns form a basis for the null space of AT(x). When A is evaluated at a given point, it is well known that a suitable Z (satisfying ATZ = 0) can be obtained from standard matrix factorizations. However, Coleman and Sorensen have recently shown that standard orthogonal factorization methods may produce orthogonal bases that do not vary continuously with x; they also suggest several techniques for adapting these schemes so as to ensure continuity of Z in the neighborhood of a given point. This paper is an extension of an earlier note that defines the procedure for computing Z. Here, we first describe how Z can be obtained by updating an explicit QR factorization with Householder transformations. The properties of this representation of Z with respect to perturbations in A are discussed, including explicit bounds on the change in Z. We then introduce regularized Householder transformations, and show that their use implies continuity of the full matrix Q. The convergence of Z and Q under appropriate assumptions is then proved. Finally, we indicate why the chosen form of Z is convenient in certain methods for nonlinearly constrained optimization.
KW - Matrix Factorization
KW - Nonlinear Optimization
KW - Null-Space Continuity
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U2 - 10.1007/BF01582244
DO - 10.1007/BF01582244
M3 - Article
AN - SCOPUS:0022162615
SN - 0025-5610
VL - 33
SP - 172
EP - 186
JO - Mathematical Programming
JF - Mathematical Programming
IS - 2
ER -