Regularization methods for unstable minimization problems based on the idea of set extension
type: Item
instance of: scholarly article
title: Regularization methods for unstable minimization problems based on the idea of set extension
zbMATH Open document ID: 0715.90088
author: F. P. Vasil'ev
published in: Moscow University Computational Mathematics and Cybernetics
publication date: 1990-01-01T00:00:00Z
review text: An optimization problem is said to be stable, or well posed, if for a small perturbation of the coefficients we obtain small variations of the solutions. Unstable or `ill-posed' problems need regularizing treatment to make them more stable. In this paper three regularization methods are studied, based on the idea of an extension of the feasible domain and estimations of the speed of convergence, with respect to the problem's functions and argument, are given for all three methods.
Mathematics Subject Classification ID: 90C31
Mathematics Subject Classification ID: 90C30
Mathematics Subject Classification ID: 90-08
zbMATH DE Number: 4179151
zbMATH Keywords: ill-posed optimization problems
zbMATH Keywords: regularization
zbMATH Keywords: extension of the feasible domain
zbMATH Keywords: speed of convergence
MaRDI profile type: Publication
description: scientific article; zbMATH DE number 4179151