Displaying similar documents to “Monotonicity of the Lagrangian function in the parametric interior point methods of convex programming.”

A numerical feasible interior point method for linear semidefinite programs

Djamel Benterki, Jean-Pierre Crouzeix, Bachir Merikhi (2007)

RAIRO - Operations Research

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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.

Rescaled proximal methods for linearly constrained convex problems

Paulo J.S. Silva, Carlos Humes (2007)

RAIRO - Operations Research

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We present an inexact interior point proximal method to solve linearly constrained convex problems. In fact, we derive a primal-dual algorithm to solve the KKT conditions of the optimization problem using a modified version of the rescaled proximal method. We also present a pure primal method. The proposed proximal method has as distinctive feature the possibility of allowing inexact inner steps even for Linear Programming. This is achieved by using an error criterion that ...

First- and second-order optimality conditions for mathematical programs with vanishing constraints

Tim Hoheisel, Christian Kanzow (2007)

Applications of Mathematics

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We consider a special class of optimization problems that we call Mathematical Programs with Vanishing Constraints, MPVC for short, which serves as a unified framework for several applications in structural and topology optimization. Since an MPVC most often violates stronger standard constraint qualification, first-order necessary optimality conditions, weaker than the standard KKT-conditions, were recently investigated in depth. This paper enlarges the set of optimality criteria...

An active set strategy based on the multiplier function or the gradient

Li Sun, Liang Fang, Guoping He (2010)

Applications of Mathematics

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We employ the active set strategy which was proposed by Facchinei for solving large scale bound constrained optimization problems. As the special structure of the bound constrained problem, a simple rule is used for updating the multipliers. Numerical results show that the active set identification strategy is practical and efficient.