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Mathematics of Computation

Published by the American Mathematical Society, the Mathematics of Computation (MCOM) is devoted to research articles of the highest quality in all areas of pure and applied mathematics.

ISSN 1088-6842 (online) ISSN 0025-5718 (print)

The 2020 MCQ for Mathematics of Computation is 1.98.

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A comparison of block pivoting and interior-point algorithms for linear least squares problems with nonnegative variables
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by Luís F. Portugal, Joaquím J. Júdice and Luís N. Vicente PDF
Math. Comp. 63 (1994), 625-643 Request permission


In this paper we discuss the use of block principal pivoting and predictor-corrector methods for the solution of large-scale linear least squares problems with nonnegative variables (NVLSQ). We also describe two implementations of these algorithms that are based on the normal equations and corrected seminormal equations (CSNE) approaches. We show that the method of normal equations should be employed in the implementation of the predictor-corrector algorithm. This type of approach should also be used in the implementation of the block principal pivoting method, but a switch to the CSNE method may be useful in the last iterations of the algorithm. Computational experience is also included in this paper and shows that both the predictor-corrector and the block principal pivoting algorithms are quite efficient to deal with large-scale NVLSQ problems.
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Additional Information
  • © Copyright 1994 American Mathematical Society
  • Journal: Math. Comp. 63 (1994), 625-643
  • MSC: Primary 90C20; Secondary 65K05
  • DOI:
  • MathSciNet review: 1250776