A numerical feasible interior point method for linear semidefinite
programs

Djamel Benterki; Jean-Pierre Crouzeix; Bachir Merikhi

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Displaying similar documents to “A numerical feasible interior point method for linear semidefinite programs”

A globally convergent non-interior point algorithm with full Newton step for second-order cone programming

Liang Fang, Guoping He, Li Sun (2009)

Applications of Mathematics

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A non-interior point algorithm based on projection for second-order cone programming problems is proposed and analyzed. The main idea of the algorithm is that we cast the complementary equation in the primal-dual optimality conditions as a projection equation. By using this reformulation, we only need to solve a system of linear equations with the same coefficient matrix and compute two simple projections at each iteration, without performing any line search. This algorithm can start...

Primal interior-point method for large sparse minimax optimization

Ladislav Lukšan, Ctirad Matonoha, Jan Vlček (2009)

Kybernetika

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In this paper, we propose a primal interior-point method for large sparse minimax optimization. After a short introduction, the complete algorithm is introduced and important implementation details are given. We prove that this algorithm is globally convergent under standard mild assumptions. Thus the large sparse nonconvex minimax optimization problems can be solved successfully. The results of extensive computational experiments given in this paper confirm efficiency and robustness...

An accurate active set Newton algorithm for large scale bound constrained optimization

Li Sun, Guoping He, Yongli Wang, Changyin Zhou (2011)

Applications of Mathematics

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A new algorithm for solving large scale bound constrained minimization problems is proposed. The algorithm is based on an accurate identification technique of the active set proposed by Facchinei, Fischer and Kanzow in 1998. A further division of the active set yields the global convergence of the new algorithm. In particular, the convergence rate is superlinear without requiring the strict complementarity assumption. Numerical tests demonstrate the efficiency and performance of the...