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Displaying similar documents to “Existence of local saddle points for a new augmented Lagrangian function.”

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 ...

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.

Random perturbation of the variable metric method for unconstrained nonsmooth nonconvex optimization

Abdelkrim El Mouatasim, Rachid Ellaia, José Souza de Cursi (2006)

International Journal of Applied Mathematics and Computer Science

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We consider the global optimization of a nonsmooth (nondifferentiable) nonconvex real function. We introduce a variable metric descent method adapted to nonsmooth situations, which is modified by the incorporation of suitable random perturbations. Convergence to a global minimum is established and a simple method for the generation of suitable perturbations is introduced. An algorithm is proposed and numerical results are presented, showing that the method is computationally effective...

Primal interior point method for minimization of generalized minimax functions

Ladislav Lukšan, Ctirad Matonoha, Jan Vlček (2010)

Kybernetika

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In this paper, we propose a primal interior-point method for large sparse generalized minimax optimization. After a short introduction, where the problem is stated, we introduce the basic equations of the Newton method applied to the KKT conditions and propose a primal interior-point method. (i. e. interior point method that uses explicitly computed approximations of Lagrange multipliers instead of their updates). Next we describe the basic algorithm and give more details concerning...

Regularization method for stochastic mathematical programs with complementarity constraints

Gui-Hua Lin, Masao Fukushima (2005)

ESAIM: Control, Optimisation and Calculus of Variations

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In this paper, we consider a class of stochastic mathematical programs with equilibrium constraints (SMPECs) that has been discussed by Lin and Fukushima (2003). Based on a reformulation given therein, we propose a regularization method for solving the problems. We show that, under a weak condition, an accumulation point of the generated sequence is a feasible point of the original problem. We also show that such an accumulation point is S-stationary to the problem under additional assumptions. ...