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L. Finschi and K. Fukuda and H.-J. Lüthi
1998 September 10
Appeared in: Operations Research Proceedings 1998 (Zurich), Springer, Berlin, pp. 113-122 (1999)
We study linear programming (LP) algorithms. Of particular interest are bounds for the number of elementary arithmetic operations necessary to solve a linear program. The best bounds that depend only on the sizes of a basis and a nonbasis have been found for a family of randomized pivoting algorithms. However, the original descriptions and analyses of these algorithms use several different geometric and abstract settings. In this paper we present a unified framework in which we describe two known algorithms as special simplex methods and analyse their complexities and differences.
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