Titlebook: Nonlinear Optimization and Related Topics; Gianni Di Pillo,Franco Giannessi Book 2000 Springer Science+Business Media Dordrecht 2000 algor

coagulate

intention

Progesterone

synovitis

Minimal Convexificators of a positively Homogeneous Function and a Characterization of Its Convexitthe convexity and concavity of .. It is shown that the uniqueness of a minimal (by inclusion) convexificator is a necessary and sufficient condition for a p.h. function to be convex or concave. Representations of a p.h. function in terms of its minimal convexificators are also derived.

AUGUR

Optimal Control Problems and Penalization,functional is essentially nonsmooth but directionally differentiable (even subdifferentiable). Differential equations are viewed as constraints and are “removed” by introducing an exact penalty function. The aim of the paper is to illustrate that well-known optimality conditions can be derived via Exact Penalty approach.

Little

Fixed and virtual stability center methods for convex nonsmooth minimization,ods involves a different approach for updating the stability center, that classically is chosen as the best current point (in terms of the objective function). Convergence to a minimum point for both methods, which are related to the concept of proximal trajectory, is proved under routine assumptions. Finally numerical results are reported.

大都市

nerve-sparing

Quadratic and Multidimensional Assignment Problems,sociation problems which are formulated as Multidimensional Assignment Problems. Computational results with two applications, the turbine balancing problem and multitarget multisensor tracking problem, are presented.

FLIC

Global Lagrange multiplier rule and smooth exact penalty functions for equality constraints,e global Lagrange multiplier rule formulated by the first and second covariant derivatives of the objective function with respect to the induced Riemannian metric of the constraint manifold. The tensor approach is described by the usual tools of nonlinear optimization giving a clearer geometric background of these methods.

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Structural Methods in the Solution of Variational Inequalities,mplify the solution of variational inequalities. As a byproduct of this approach we recover as special cases a number of known methods, including the Schur complement and the Sherman-Morrison-Woodbury formula for inverting perturbed matrices.