An application of semi-infinite linear programming: approximation of a continuous function by a polynomial
An approach to robust network design in telecommunications
In telecommunications network design, one of the most frequent problems is to adjust the capacity on the links of the network in order to satisfy a set of requirements. In the past, these requirements were demands based on historical data and/or demographic predictions. Nowadays, because of new technology development and customer movement due to competitiveness, the demands present considerable variability. Thus, network robustness w.r.t demand uncertainty is now regarded as a major consideration....
An Approximation Technique for the Numerical Solution of a Stefan Problem.
An approximative method for solving the non-linear optimal control problem
An efficiency analysis of the parallel multitransputer implementation of two-level optimization algorithms
The paper presents an approach to improve the efficiency of some two-level optimization algorithms by their implementation in parallel MIMD multiprocessor systems. Diagonal decomposition dynamic programming and parametric optimization methods are considered, and some concepts of their parallelization are discussed. Results regarding the implementation of computations in a parallel multitransputer system are presented. For the analysed problems, the obtained values of speedup are close to the theoretical...
An Efficient Method for Calculating Smoothing Splines Using Orthogonal Transformations.
An entropic regularization method for solving systems of fuzzy linear inequalities.
An error estimation for the method of bisection in IR^n
An imperfect conjugate gradient algorithm
A new biorthogonalization algorithm is defined which does not depend on the step-size used. The algorithm is suggested so as to minimize the total error after steps if imperfect steps are used. The majority of conjugate gradient algorithms are sensitive to the exactness of the line searches and this phenomenon may destroy the global efficiency of these algorithms.
An implementation of recursive quadratic programming variable metric methods for linearly constrained nonlinear minimax approximation
An Interactive Algorithm for Large Scale Multiple Objective Programming Problems With Fuzzy Parameters Through Topsis Approach
An interior-point algorithm for semidefinite least-squares problems
We propose a feasible primal-dual path-following interior-point algorithm for semidefinite least squares problems (SDLS). At each iteration, the algorithm uses only full Nesterov-Todd steps with the advantage that no line search is required. Under new appropriate choices of the parameter which defines the size of the neighborhood of the central-path and of the parameter which determines the rate of decrease of the barrier parameter, we show that the proposed algorithm is well defined and converges...
An Interval Arithmetic Algorithm for Multivariate Constrained Global Optimization Using Cord-Slope Forms of Taylor's Expansion
An iterative algorithm of solution for quadratic minimization problem in Hilbert spaces.
An Iterative Procedure for the Solution of Constrained Nonlinear Equations with Application to Optimization Problems.
Analysis of a non-monotone smoothing-type algorithm for the second-order cone programming
The smoothing-type algorithm is a powerful tool for solving the second-order cone programming (SOCP), which is in general designed based on a monotone line search. In this paper, we propose a smoothing-type algorithm for solving the SOCP with a non-monotone line search. By using the theory of Euclidean Jordan algebras, we prove that the proposed algorithm is globally and locally quadratically convergent under suitable assumptions. The preliminary numerical results are also reported which indicate...
Analysis of some Krylov subspace methods for normal matrices via approximation theory and convex optimization.
Anmerkungen zu einem Mehrgitterverfahren für lineare Komplementaritätsprobleme.
Approximate solution of stochastic programming problems with recourse
Approximations to Stochastic Programs with Complete Fixed Recourse.