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.
Study of stationary solutions in gene network models by the homotopy method.
Subgradient optimization and large scale programming : an application to optimum multicommodity network synthesis with security constraints
Sufficient decrease principle on Riemannian manifolds.
Superconvergence analysis and a posteriori error estimation of a Finite Element Method for an optimal control problem governed by integral equations
In this paper, we discuss the numerical simulation for a class of constrained optimal control problems governed by integral equations. The Galerkin method is used for the approximation of the problem. A priori error estimates and a superconvergence analysis for the approximation scheme are presented. Based on the results of the superconvergence analysis, a recovery type a posteriori error estimator is provided, which can be used for adaptive mesh refinement.
Superconvergence estimates of finite element methods for American options
In this paper we are concerned with finite element approximations to the evaluation of American options. First, following W. Allegretto etc., SIAM J. Numer. Anal. 39 (2001), 834–857, we introduce a novel practical approach to the discussed problem, which involves the exact reformulation of the original problem and the implementation of the numerical solution over a very small region so that this algorithm is very rapid and highly accurate. Secondly by means of a superapproximation and interpolation...
Superlinear Convergence of Symmetric Huang's Class of Methods.
Sur la convergence de la méthode d'Adomian
Sur la convergence théorique de la méthode du gradient réduit généralisé.
Sur la dérivation numérique en optimisation
Sur la méthode de sur-relaxation, dans le cas des problèmes avec contrainte : un résultat de convergence asymptotique
Symplectic Pontryagin approximations for optimal design
The powerful Hamilton-Jacobi theory is used for constructing regularizations and error estimates for optimal design problems. The constructed Pontryagin method is a simple and general method for optimal design and reconstruction: the first, analytical, step is to regularize the hamiltonian; next the solution to its stationary hamiltonian system, a nonlinear partial differential equation, is computed with the Newton method. The method is efficient for designs where the hamiltonian function can be...