Sparse Linear Least Squares Problems in Optimization

Matstoms, Pontus

doi:10.1007/978-0-585-26778-4_6

Cited by 1 publication

(1 citation statement)

References 40 publications

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“…The LQ factorization in spLQ relies on the work of Matstoms [1994]; see also Matstoms [1997]. For completeness we give a rough outline of the algorithm along with some notes on the implementation strategies.…”

Section: Multifrontal Factorizationmentioning

confidence: 99%

A software package for sparse orthogonal factorization and updating

Edlund

2002

ACM Trans. Math. Softw.

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Although there is good software for sparse QR factorization, there is little support for updating and downdating, something that is absolutely essential in some linear programming algorithms, for example. This article describes an implementation of sparse LQ factorization, including block triangularization, approximate minimum degree ordering, symbolic factorization, multifrontal factorization, and updating and downdating. The factor Q is not retained. The updating algorithm expands the nonzero pattern of the factor L, which is reflected in dynamic representation of L. The block triangularization is used as an "ordering for sparsity" rather than as a prerequisite for block backward substitution. In symbolic factorization, something called "element counters" is introduced to reduce the overestimation of the number of nonzeros that the commonly used methods do. Both the approximate minimum degree ordering and the symbolic factorization are done without explicitly forming the nonzero pattern of the symmetric matrix in the corresponding normal equations. Tests show that the average time used for a single update or downdate is essentially the same as the time used for a single forward or backward substitution. Other parts of the implementation show the same range of performance as existing code, but cannot be replaced because of the special character of the systems that are solved.

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Section: Multifrontal Factorizationmentioning

confidence: 99%

A software package for sparse orthogonal factorization and updating

Edlund

2002

ACM Trans. Math. Softw.

View full text Add to dashboard Cite

show abstract

Sparse Linear Least Squares Problems in Optimization

Cited by 1 publication

References 40 publications

A software package for sparse orthogonal factorization and updating

A software package for sparse orthogonal factorization and updating

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