Some iterative methods for solving equilibrium problems and optimization problems.
Some notes on the quasi-Newton methods
A survey note whose aim is to establish the heuristics and natural relations in a class of Quasi-Newton methods in optimization problems. It is shown that a particular algorithm of the class is specified by characcterizing some parameters (scalars and matrices) in a general solution of a matrix equation.
Some numerical methods for the study of the convexity notions arising in the calculus of variations
Some optimization problems on solubility sets of separable Max-Min equations and inequalities
Sparse Null Basis Computations in Structural Optimization.
Stability of lagrangian duality for nonconvex quadratic programming. Solution methods and applications in computer vision
Stability of microstructure for tetragonal to monoclinic martensitic transformations
Stability of microstructure for tetragonal to monoclinic martensitic transformations
We give an analysis of the stability and uniqueness of the simply laminated microstructure for all three tetragonal to monoclinic martensitic transformations. The energy density for tetragonal to monoclinic transformations has four rotationally invariant wells since the transformation has four variants. One of these tetragonal to monoclinic martensitic transformations corresponds to the shearing of the rectangular side, one corresponds to the shearing of the square base, and one corresponds to...
Stability of saddle point problems with penalty
Stabilization methods in relaxed micromagnetism
The magnetization of a ferromagnetic sample solves a non-convex variational problem, where its relaxation by convexifying the energy density resolves relevant macroscopic information. The numerical analysis of the relaxed model has to deal with a constrained convex but degenerated, nonlocal energy functional in mixed formulation for magnetic potential and magnetization . In [C. Carstensen and A. Prohl, Numer. Math. 90 (2001) 65–99], the conforming -element in spatial dimensions is shown to...
Stabilization methods in relaxed micromagnetism
The magnetization of a ferromagnetic sample solves a non-convex variational problem, where its relaxation by convexifying the energy density resolves relevant macroscopic information. The numerical analysis of the relaxed model has to deal with a constrained convex but degenerated, nonlocal energy functional in mixed formulation for magnetic potential u and magnetization m. In [C. Carstensen and A. Prohl, Numer. Math.90 (2001) 65–99], the conforming P1 - (P0)d-element in d=2,3 spatial dimensions...
Stable approximations of a minimal surface problem with variational inequalities.
Stable evaluation of differential operators and linear and nonlinear multi-scale filtering.
Staging in Balas' algorithm
Statical moments of exact and approximate profiles of air springs
Strategies for LP-based solving a general class of scheduling problems.
In this work we describe some strategies that have been proved to be very efficient for solving the following type of scheduling problems: Assume a set of jobs is to be performed along a planning horizon by selecting one from several alternatives for doing so. Besides selecting the alternative for each job, the target consists of choosing the periods at which each component of the work will be done, such that a set of scheduling and technological constraints is satisfied. The problem is formulated...
Strong convergence of a new iterative method for infinite family of generalized equilibrium and fixed-point problems of nonexpansive mappings in Hilbert spaces.
Strong Uniqueness and Second Order Convergence in Nonlinear Discrete Approximation.
Structural optimization using topological and shape sensitivity via a level set method
Structural Properties of Solutions to Total Variation Regularization Problems
In dimension one it is proved that the solution to a total variation-regularized least-squares problem is always a function which is "constant almost everywhere" , provided that the data are in a certain sense outside the range of the operator to be inverted. A similar, but weaker result is derived in dimension two.