A recursive quadric programming algorithm that uses new nondifferentiable penalty functions
type: Item
instance of: scholarly article
title: A recursive quadric programming algorithm that uses new nondifferentiable penalty functions
zbMATH Open document ID: 0809.49031
DOI: 10.1007/BF02662030
author: Boting Yang
author: Kecun Zhang
published in: Applied Mathematics. Series B (English Edition)
publication date: 1994-10-24T00:00:00Z
review text: The problem considered in this paper is the equality-constrained nonlinear programming problem \[ \text{minimize } f(x)\text{ subject to } C(x)= 0,\tag{P} \] where \(f: \mathbb{R}^ n\to \mathbb{R}\), \(C: \mathbb{R}^ n\to \mathbb{R}^ m\) are twice continuously differentiable. For the solution of (P) a recursive quadratic programming algorithm is proposed which uses Han's nondifferentiable penalty functions together with a second order penalty term and Fukushima's mixed direction as the line search direction. Finally, under some particular assumptions, the method is proved to be globally convergent as well as locally convergent of second order.
Mathematics Subject Classification ID: 49M37
Mathematics Subject Classification ID: 90C30
Mathematics Subject Classification ID: 90C20
zbMATH DE Number: 640430
zbMATH Keywords: equality-constrained nonlinear programming
zbMATH Keywords: quadratic programming
reviewed by: Reinhardt Euler
MaRDI profile type: Publication
cites work: A globally convergent method for nonlinear programming
cites work: A successive quadratic programming algorithm with global and superlinear convergence properties
cites work: Q3928936
full work available at URL: https://doi.org/10.1007/bf02662030
OpenAlex ID: W1972983088
description: scientific article; zbMATH DE number 640430