IJPAM: Volume 77, No. 3 (2012)
ALGORITHMS FOR THE CONVEXE
University of Setif
Setif, 19000, ALGERIA
Abstract. In this paper we propose a method for convex quadratic programming with the property that starting from an initial feasible point, it generates iterates that simultaneously get closer to optimality and closer to centrality. The iterates follow so-called targets, that are updated with Short-steps. Newton's method is used to find an iterate close to a target. We propose an algorithm with the best theoretical polynomial complexity namely O(log( , iteration bound. For its numerical performances some strategies are used. Finally, we have tested this algorithm on some convexe quadratique problems.
Received: November 25, 2011
AMS Subject Classification: 65K05, 90C20, 90C51
Key Words and Phrases: interior points methods, convex quadratic programming, short-step method, primal-dual target following algorithm, polynomial complexity
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Source: International Journal of Pure and Applied Mathematics
ISSN printed version: 1311-8080
ISSN on-line version: 1314-3395