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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

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 and stable....

Reformulations in Mathematical Programming: Definitions and Systematics

Leo Liberti (2009)

RAIRO - Operations Research

A reformulation of a mathematical program is a formulation which shares some properties with, but is in some sense better than, the original program. Reformulations are important with respect to the choice and efficiency of the solution algorithms; furthermore, it is desirable that reformulations can be carried out automatically. Reformulation techniques are widespread in mathematical programming but interestingly they have never been studied under a unified framework. This paper attempts to move...

Regularization in state space

G. Chavent, K. Kunisch (1993)

ESAIM: Mathematical Modelling and Numerical Analysis - Modélisation Mathématique et Analyse Numérique

Regularization method for stochastic mathematical programs with complementarity constraints

Gui-Hua Lin, Masao Fukushima (2005)

ESAIM: Control, Optimisation and Calculus of Variations

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.

Regularization method for stochastic mathematical programs with complementarity constraints

Gui-Hua Lin, Masao Fukushima (2010)

ESAIM: Control, Optimisation and Calculus of Variations

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....

Robust preconditioners for the matrix free truncated Newton method

Lukšan, Ladislav, Matonoha, Ctirad, Vlček, Jan (2010)

Programs and Algorithms of Numerical Mathematics

New positive definite preconditioners for the matrix free truncated Newton method are given. Corresponding algorithms are described in detail. Results of numerical experiments that confirm the efficiency and robustness of the preconditioned truncated Newton method are reported.

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