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Mathematics of Computation

Published by the American Mathematical Society since 1960 (published as Mathematical Tables and other Aids to Computation 1943-1959), Mathematics of Computation is devoted to research articles of the highest quality in computational mathematics.

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

The 2020 MCQ for Mathematics of Computation is 1.78.

What is MCQ? The Mathematical Citation Quotient (MCQ) measures journal impact by looking at citations over a five-year period. Subscribers to MathSciNet may click through for more detailed information.

 

Two linear programming algorithms for the linear discrete $L_{1}$ norm problem
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by Ronald D. Armstrong and James P. Godfrey PDF
Math. Comp. 33 (1979), 289-300 Request permission

Abstract:

Computational studies by several authors have indicated that linear programming is currently the most efficient procedure for obtaining ${L_1}$, norm estimates for a discrete linear problem. However, there are several linear programming algorithms, and the "best" approach may depend on the problem’s structure (e.g., sparsity, triangularity, stability). In this paper we shall compare two published simplex algorithms, one referred to as primal and the other referred to as dual, and show that they are conceptually equivalent.
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Additional Information
  • © Copyright 1979 American Mathematical Society
  • Journal: Math. Comp. 33 (1979), 289-300
  • MSC: Primary 90C05
  • DOI: https://doi.org/10.1090/S0025-5718-1979-0525398-2
  • MathSciNet review: 0525398