This paper aims at showing that the class of augmented Lagrangian functions for nonlinear semidefinite programming problems can be derived, as a particular case, from a nonlinear separation scheme in the image space associated with the given problem. By means of the image space analysis, a...

The paper proposes a primal-dual algorithm for solving an equality constrained minimization problem. The algorithm is a Newton-like method applied to a sequence of perturbed optimality systems that follow naturally from the quadratic penalty approach. This work is first motivated by the fact...

Abstract Consider Z i  = ( X i , Y i ), i  ∈ ℤ N be an F×ℝ-valued measurable strictly stationary spatial process, where F is a semi-metric space. We study the spatial covariation between X i and Y i by using the local linear estimate of the functional spatial regression E[ Y i | X i...

This paper presents some applications of the canonical dual theory in optimal control problems. The analytic solutions of several nonlinear and nonconvex problems are investigated by global optimizations. It turns out that the backward differential flow defined by the KKT equation may reach the...

Linear programming problems with fuzzy variables have been investigated by many researchers in the recent literature. Some methods to solve these problems, such as the primal simplex method and the dual simplex method, are based on the concept of comparison of fuzzy numbers by using ranking...

Michele De Benedictis has for some time taken an interest in behavioral models for agricultural entrepreneurs. Often, such models are specified by means of a production function and a cost function with the associated derived demands for inputs. In order to make such models operational in a...