Convergence analysis of a nonlinear Lagrangian algorithm for nonlinear programming with inequality constraints
type: Item
instance of: scholarly article
title: Convergence analysis of a nonlinear Lagrangian algorithm for nonlinear programming with inequality constraints
zbMATH Open document ID: 1044.90079
DOI: 10.1007/BF02936070
author: Yong-Jin Liu
author: Liwei Zhang
published in: Journal of Applied Mathematics and Computing
publication date: 2004-05-18T00:00:00Z
review text: This paper establishes a nonlinear Lagrangian algorithm for nonlinear programming problems with inequality constraints. By using a nonlinear Lagrangian function, in each iteration an easier (unconstrained) minimization problem is used to obtain an iteration point. Then, under some mild assumptions, the local convergence of such iterations points to a Kuhn-Tucker point of the primal nonlinear programming problem is proved.
Mathematics Subject Classification ID: 90C30
Mathematics Subject Classification ID: 90C26
zbMATH DE Number: 2064688
zbMATH Keywords: nonlinear Lagrangian algorithm
zbMATH Keywords: nonlinear programming
zbMATH Keywords: nonlinear Lagrangian function
reviewed by: Fabián Flores-Bazan
MaRDI profile type: Publication
cites work: Q3690580
cites work: Q3151174
cites work: On the formulation and theory of the Newton interior-point method for nonlinear programming
cites work: Modified barrier functions (theory and methods)
cites work: Q-SUPERLINEAR CONVERGENCE OF PRIMAL-DUAL INTERIOR POINT QUASI-NEWTON METHODS FOR CONSTRAINED OPTIMIZATION
cites work: Superlinear and quadratic convergence of some primal - dual interior point methods for constrained optimization
cites work: Q4519027
full work available at URL: https://doi.org/10.1007/bf02936070
OpenAlex ID: W1976652812
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description: scientific article; zbMATH DE number 2064688