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A numerical feasible interior point method for linear semidefiniteprograms

Published online by Cambridge University Press:  15 June 2007

Djamel Benterki ,
Jean-Pierre Crouzeix  and
Bachir Merikhi
Djamel Benterki
Affiliation:
Département de Mathématiques, Faculté des sciences, Université Ferhat Abbas, Sétif, 19000, Algérie ; dj_benterki@yahoo.fr; b_merikhi@yahoo.fr
Jean-Pierre Crouzeix
Affiliation:
LIMOS, Université Blaise Pascal, 63177 Aubière Cedex, France; jp.crouzeix@math.univ-bpclermont.fr
Bachir Merikhi
Affiliation:
Département de Mathématiques, Faculté des sciences, Université Ferhat Abbas, Sétif, 19000, Algérie ; dj_benterki@yahoo.fr; b_merikhi@yahoo.fr
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Abstract

This paper presents a feasible primal algorithm for linear semidefinite programming. The algorithm starts with a strictly feasible solution, but in case where no such a solution is known, an application of the algorithm to an associate problem allows to obtain one. Finally, we present some numerical experiments which show that the algorithm works properly.

Keywords

Linear programmingsemidefinite programminginterior point methods.

Information

Type
Research Article
Information
RAIRO - Operations Research , Volume 41 , Issue 1 , January 2007 , pp. 49 - 59
Copyright
© EDP Sciences, ROADEF, SMAI, 2007

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