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Numerical Algorithms

, Volume 70, Issue 2, pp 393–405 | Cite as

Complexity analysis and numerical implementation of a full-Newton step interior-point algorithm for LCCO

  • Mohamed Achache
  • Moufida Goutali
Original Paper

Abstract

In this paper, we present a primal-dual interior point algorithm for linearly constrained convex optimization (LCCO). The algorithm uses only full-Newton step to update iterates with an appropriate proximity measure for controlling feasible iterations near the central path during the solution process. The favorable polynomial complexity bound for the algorithm with short-step method is obtained, namely \(O(\sqrt {n}\log \frac {n}{\epsilon })\) which is as good as the linear and convex quadratic optimization analogue. Numerical results are reported to show the efficiency of the algorithm.

Keywords

Linearly constrained convex optimization Interior point methods Short-step primal-dual algorithms Complexity of algorithms 

Mathematical Subject Classifications (2010)

90C25 90C51 

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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Laboratoire de Mathématiques Fondamentales et NumériquesUniversité Ferhat Abbas de Sétif1SétifAlgérie
  2. 2.Département de Mathématiques, Faculté des SciencesUniversité Ferhat Abbas de Sétif1SétifAlgérie

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