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Abstract: A mechanism for proving global convergence in filter-type methods for nonlinear programming is described. Such methods are characterized by their use of the dominance concept of multiobjective optimization, instead of a penalty parameter whose adjustment can be problematic. The main point of interest is to demonstrate how convergence for NLP can be induced without forcing sucient descent in a penalty-type merit function. The proof relates to a prototypical algorithm, within which is allowed a... (Update)
Context of citations to this paper: More
...e ect on practical performance. Here we use the type of test suggested originally by Chin and Fletcher [1] and used by Fletcher, Ley er and Toint [3]. Thus the condition for a point 6 R. Fletcher and S. Ley er being acceptable to the lter is that its (h; f) pair satis es...
...the basis of a commercial NLP code. There exist some other papers, Fletcher, Gould, Ley er and Toint [3] and Fletcher, Ley er and Toint [6], that address the issue of global convergence for trust region SQP lter methods. Our paper here has some new features. One useful idea...
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Interior-Point l_2-Penalty Methods for Nonlinear Programming.. - Chen, Goldfarb (2004) (Correct)
On the Superlinear Local Convergence of a Filter-SQP Method - Ulbrich (2002) (Correct)
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4: Nonlinear programming without a penalty function - Fletcher, Leyffer - 1997
2: A globally convergent filter method for nonlinear programming (context) - GONZAGA, KARAS et al. - 2002
2: Watson Research Center (context) - Paterson, Wegman et al. - 1976
BibTeX entry: (Update)
Fletcher R., Ley er S. and Toint Ph.L. (2000), On the Global Convergence of a Filter{SQP Algorithm, Dundee University, Dept. of Mathematics, Report NA/197, to appear in SIAM Journal of Optimization. http://citeseer.ist.psu.edu/fletcher00global.html More
@misc{ fletcher00global,
author = "R. Fletcher and S. Leyffer and Ph. Toint",
title = "On the Global Convergence of a Filter-{SQP} Algorithm",
note = "Dundee University, Dept. of Mathematics, Report
NA/197, to appear in {SIAM} Journal of Optimization.",
year = "2000",
url = "citeseer.ist.psu.edu/fletcher00global.html" }
Citations (may not include all citations):119 Nonlinear Programming (context) - Mangasarian - 1969
58 Nonlinear Programming Without a Penalty Function - Fletcher, Ley - 1997
24 Trust Region Methods (context) - Conn, Gould et al. - 2000
12 the Global Convergence of an SLP{Filter Algorithm - Fletcher, Ley et al. - 1999
10 A Trust Region Method for Solving Generalized Complementarit.. (context) - Jiang, Fukushima et al. - 1998
10 An Algorithm for Minimax Solution of Overdetermined Systems .. (context) - Madsen
8 Nonlinear programming and nonsmooth optimization by successi.. (context) - Fletcher - 1989
6 Inexact Trust-Region Methods for Nonlinear Complementarity P.. - Ch - 1997
5 A necessary and sucient regularity condition to have bounded.. (context) - Gauvin - 1977
2 Global convergence of trust-region SQP-lter algorithms for n.. (context) - Fletcher, Gould et al. - 1999
1 Convergence Properties of SLP{Filter Algorithms that use EQP.. (context) - Chin, Fletcher - 2000
Documents on the same site (http://www.mcs.dundee.ac.uk:8080/~sleyffer): More
Generalized Outer Approximation - Leyffer (Correct)
Nonlinear Programming without a penalty function - Fletcher, Leyffer (1998) (Correct)
On the Global Convergence of an SLP-Filter Algorithm - Fletcher, Leyffer, Toint (1998) (Correct)
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