Expected Number of Iterations of Interior-Point Algorithms for Linear Programming

Expected Number of Iterations of Interior-Point Algorithms for Linear Programming

Year:    2005

Journal of Computational Mathematics, Vol. 23 (2005), Iss. 1 : pp. 93–100

Abstract

We study the behavior of some polynomial interior-point algorithms for solving random linear programming (LP) problems. We show that the expected and anticipated number of iterations of these algorithms is bounded above by $O(n^{1.5})$. The random LP problem is Todd's probabilistic model with the Cauchy distribution.

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Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/2005-JCM-8799

Journal of Computational Mathematics, Vol. 23 (2005), Iss. 1 : pp. 93–100

Published online:    2005-01

AMS Subject Headings:   

Copyright:    COPYRIGHT: © Global Science Press

Pages:    8

Keywords:    Linear programming Interior point algorithms Probabilistic LP models Expected number of iterations.