Please use this identifier to cite or link to this item: https://doi.org/10.1007/s10957-005-2092-4
Title: Global convergence analysis of line search interior-point methods for nonlinear programming without regularity assumptions
Authors: Liu, X.W. 
Sun, J. 
Keywords: Convergence
Interior-point methods
Nonlinear programming
Issue Date: 2005
Source: Liu, X.W., Sun, J. (2005). Global convergence analysis of line search interior-point methods for nonlinear programming without regularity assumptions. Journal of Optimization Theory and Applications 125 (3) : 609-628. ScholarBank@NUS Repository. https://doi.org/10.1007/s10957-005-2092-4
Abstract: As noted by Wächter and Biegler (Ref. 1), a number of interior-point methods for nonlinear programming based on line-search strategy may generate a sequence converging to an infeasible point. We show that, by adopting a suitable merit function, a modified primal-dual equation, and a proper line-search procedure, a class of interior-point methods of line-search type will generate a sequence such that either all the limit points of the sequence are KKT points, or one of the limit points is a Fritz John point, or one of the limit points is an infeasible point that is a stationary point minimizing a function measuring the extent of violation to the constraint system. The analysis does not depend on the regularity assumptions on the problem. Instead, it uses a set of satisfiable conditions on the algorithm implementation to derive the desired convergence property. © 2005 Springer Science+Business Media, Inc.
Source Title: Journal of Optimization Theory and Applications
URI: http://scholarbank.nus.edu.sg/handle/10635/44227
ISSN: 00223239
DOI: 10.1007/s10957-005-2092-4
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