A Trust Region Method Using Subgradient for Minimizing a Nondifferentiable Function

Milanka Gardašević Filipović

Displaying similar documents to “A Trust Region Method Using Subgradient for Minimizing a Nondifferentiable Function”

Reverse convex problems: an approach based on optimality conditions.

Tseveendorj, Ider (2006)

Journal of Applied Mathematics and Decision Sciences

Similarity:

An Algorithm for $L C^{1}$ Optimization

Nada I. Đuranović-Miličić (2005)

The Yugoslav Journal of Operations Research

Similarity:

A Multi –Step Curve Search Algorithm in Nonlinear Optimization

Nada I. Đuranović-Miličić (2008)

The Yugoslav Journal of Operations Research

Similarity:

A PVT-Type Algorithm for Minimizing a Nonsmooth Convex Function

Pang, Li-Ping, Xia, Zun-Quan (2003)

Serdica Mathematical Journal

Similarity:

2000 Mathematics Subject Classification: 90C25, 68W10, 49M37. A general framework of the (parallel variable transformation) PVT-type algorithm, called the PVT-MYR algorithm, for minimizing a non-smooth convex function is proposed, via the Moreau-Yosida regularization. As a particular scheme of this framework an ε-scheme is also presented. The global convergence of this algorithm is given under the assumptions of strong convexity of the objective function and an ε-descent...

Solving convex program via Lagrangian decomposition

Matthias Knobloch (2004)

Kybernetika

Similarity:

We consider general convex large-scale optimization problems in finite dimensions. Under usual assumptions concerning the structure of the constraint functions, the considered problems are suitable for decomposition approaches. Lagrangian-dual problems are formulated and solved by applying a well-known cutting-plane method of level-type. The proposed method is capable to handle infinite function values. Therefore it is no longer necessary to demand the feasible set with respect to the...