A globally convergent algorithm for nonlinearly constrained optimization problems
type: Item
instance of: scholarly article
title: A globally convergent algorithm for nonlinearly constrained optimization problems
zbMATH Open document ID: 0585.90076
DOI: 10.1007/BF00941288
author: M. Sahba
published in: Journal of Optimization Theory and Applications
publication date: 1987-01-01T00:00:00Z
review text: A new globally convergent algorithm for minimizing an objective function subject to equality and inequality constraints is presented. The algorithm determines a search direction by first solving a linear program and using the information gained thereby to define a quadratic approximation, with a guaranteed solution, to the original problem; the solution of the quadratic problem is the desired search direction. The algorithm incorporates a new method for choosing the penalty parameter. Numerical results illustrate the performance of the algorithm.
Mathematics Subject Classification ID: 90C30
Mathematics Subject Classification ID: 49M37
Mathematics Subject Classification ID: 65K05
zbMATH DE Number: 3939108
zbMATH Keywords: quadratic approximation
zbMATH Keywords: globally convergent algorithm
zbMATH Keywords: equality and inequality constraints
zbMATH Keywords: constrained optimization
zbMATH Keywords: exact penalty functions
MaRDI profile type: Publication
cites work: A globally convergent method for nonlinear programming
cites work: A surperlinearly convergent algorithm for constrained optimization problems
cites work: The watchdog technique for forcing convergence in algorithms for constrained optimization
cites work: An Exact Potential Method for Constrained Maxima
cites work: Q4151662
cites work: Some examples of cycling in variable metric methods for constrained minimization
cites work: An efficient algorithm for solving inequalities
cites work: Q5672476
cites work: Perturbed Kuhn-Tucker points and rates of convergence for a class of nonlinear-programming algorithms
cites work: Superlinearly convergent quasi-newton algorithms for nonlinearly constrained optimization problems
cites work: The nonlinear programming method of Wilson, Han, and Powell with an augmented Lagrangian type line search function. I. Convergence analysis
cites work: Q5652460
cites work: Q5588268
cites work: Q3932225
cites work: Q3690580
cites work: Nonlinear programming via an exact penalty function: Asymptotic analysis
cites work: Nonlinear programming via an exact penalty function: Global analysis
description: scientific article; zbMATH DE number 3939108