-error estimate for a discrete two-sided obstacle problem and multilevel projective algorithm.
Large-scale Kalman filtering using the limited memory BFGS method.
Least regret control, virtual control and decomposition methods
Least regret control, virtual control and decomposition methods
"Least regret control" consists in trying to find a control which "optimizes the situation" with the constraint of not making things too worse with respect to a known reference control, in presence of more or less significant perturbations. This notion was introduced in [7]. It is recalled on a simple example (an elliptic system, with distributed control and boundary perturbation) in Section 2. We show that the problem reduces to a standard optimal control problem for augmented state equations. On...
L...-Error Estimate for an Approximation of a Parabolic Variational Inequality.
Limited-memory variable metric methods that use quantities from the preceding iteration
Linear complementarity problem and extremal hyperplanes
Linear convergence in the approximation of rank-one convex envelopes
A linearly convergent iterative algorithm that approximates the rank-1 convex envelope of a given function , i.e. the largest function below which is convex along all rank-1 lines, is established. The proposed algorithm is a modified version of an approximation scheme due to Dolzmann and Walkington.
Linear convergence in the approximation of rank-one convex envelopes
A linearly convergent iterative algorithm that approximates the rank-1 convex envelope of a given function , i.e. the largest function below f which is convex along all rank-1 lines, is established. The proposed algorithm is a modified version of an approximation scheme due to Dolzmann and Walkington.
LMS-Newton adaptive filtering using FFT-based conjugate gradient iterations.
Local analysis of a cubically convergent method for variational inclusions
This paper deals with variational inclusions of the form 0 ∈ φ(x) + F(x) where φ is a single-valued function admitting a second order Fréchet derivative and F is a set-valued map from to the closed subsets of . When a solution z̅ of the previous inclusion satisfies some semistability properties, we obtain local superquadratic or cubic convergent sequences.
Local convergence analysis for a certain class of inexact methods.
Local minimizers of functionals with multiple volume constraints
We study variational problems with volume constraints, i.e., with level sets of prescribed measure. We introduce a numerical method to approximate local minimizers and illustrate it with some two-dimensional examples. We demonstrate numerically nonexistence results which had been obtained analytically in previous work. Moreover, we show the existence of discontinuous dependence of global minimizers from the data by using a Γ-limit argument and illustrate this with numerical computations. Finally...
Mathematical Modeling of Atmospheric Flow and Computation of Convex Envelopes
Atmospheric flow equations govern the time evolution of chemical concentrations in the atmosphere. When considering gas and particle phases, the underlying partial differential equations involve advection and diffusion operators, coagulation effects, and evaporation and condensation phenomena between the aerosol particles and the gas phase. Operator splitting techniques are generally used in global air quality models. When considering organic aerosol...
Mathematical modeling of delamination and nonmonotone friction problems by hemivariational inequalities
The paper deals with approximations and the numerical realization of a class of hemivariational inequalities used for modeling of delamination and nonmonotone friction problems. Assumptions guaranteeing convergence of discrete models are verified and numerical results of several model examples computed by a nonsmooth variant of Newton method are presented.
Maximum norm analysis of an overlapping nonmatching grids method for the obstacle problem.
Meta-optimization of bio-inspired algorithms for antenna array design
In this article, a technique called Meta-Optimization is used to enhance the effectiveness of bio-inspired algorithms that solve antenna array synthesis problems. This technique consists on a second optimization layer that finds the best behavioral parameters for a given algorithm, which allows to achieve better results. Bio-inspired computational methods are useful to solve complex multidimensional problems such as the design of antenna arrays. However, their performance depends heavily on the...
Metodi lagrangiani per problemi di controllo ottimo nel discreto
Minimal invasion: An optimal L∞ state constraint problem
In this work, the least pointwise upper and/or lower bounds on the state variable on a specified subdomain of a control system under piecewise constant control action are sought. This results in a non-smooth optimization problem in function spaces. Introducing a Moreau-Yosida regularization of the state constraints, the problem can be solved using a superlinearly convergent semi-smooth Newton method. Optimality conditions are derived, convergence of the Moreau-Yosida regularization is proved, and...
Minimal invasion: An optimal L∞ state constraint problem
In this work, the least pointwise upper and/or lower bounds on the state variable on a specified subdomain of a control system under piecewise constant control action are sought. This results in a non-smooth optimization problem in function spaces. Introducing a Moreau-Yosida regularization of the state constraints, the problem can be solved using a superlinearly convergent semi-smooth Newton method. Optimality conditions are derived, convergence of the Moreau-Yosida regularization is proved, and...