Optimisation connexe en dimension finie par relaxation
Optimization analysis involving set functions.
Optimization of positive generalized polynomials under constraints.
Optimizing second-order differential equation systems.
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Parallel synchronous algorithm for nonlinear fixed point problems.
Penalties, Lagrange multipliers and Nitsche mortaring
Penalty methods, augmented Lagrangian methods and Nitsche mortaring are well known numerical methods among the specialists in the related areas optimization and finite elements, respectively, but common aspects are rarely available. The aim of the present paper is to describe these methods from a unifying optimization perspective and to highlight some common features of them.
Perturbation theory of duality in vector optimization via the abstract duality scheme
Piecewise-polynomial signal segmentation using convex optimization
A method is presented for segmenting one-dimensional signal whose independent segments are modeled as polynomials, and which is corrupted by additive noise. The method is based on sparse modeling, the main part is formulated as a convex optimization problem and is solved by a proximal splitting algorithm. We perform experiments on simulated and real data and show that the method is capable of reliably finding breakpoints in the signal, but requires careful tuning of the regularization parameters...
Polynomial algorithms for projecting a point onto a region defined by a linear constraint and box constraints in .
Problème des inégalités. Applications à la programmation et au contrôle optimal
Projection method with level control in convex minimization
We study a projection method with level control for nonsmoooth convex minimization problems. We introduce a changeable level parameter to level control. The level estimates the minimal value of the objective function and is updated in each iteration. We analyse the convergence and estimate the efficiency of this method.
Projection method with residual selection for linear feasibility problems
We propose a new projection method for linear feasibility problems. The method is based on the so called residual selection model. We present numerical results for some test problems.
Properties of projection and penalty methods for discretized elliptic control problems
In this paper, properties of projection and penalty methods are studied in connection with control problems and their discretizations. In particular, the convergence of an interior-exterior penalty method applied to simple state constraints as well as the contraction behavior of projection mappings are analyzed. In this study, the focus is on the application of these methods to discretized control problem.
Prox-mappings associated with a pair of Legendre conjugate functions
Quadratic growth and stability in convex programming problems with multiple solutions.