Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/4764
Title: A truncated projected Newton-type algorithm for large-scale semi-infinite programming
Authors: Ni, Q
Ling, C
Qi, L 
Teo, KL
Keywords: Semi-infinite programming
Karush–Kuhn–Tucker system
Large-scale problem
Issue Date: 2006
Publisher: Society for Industrial and Applied Mathematics
Source: SIAM journal on optimization, 2006, v. 16, no. 4, p. 1137-1154 How to cite?
Journal: SIAM journal on optimization 
Abstract: In this paper, a truncated projected Newton-type algorithm is presented for solving large-scale semi-infinite programming problems. This is a hybrid method of a truncated projected Newton direction and a modified projected gradient direction. The truncated projected Newton method is used to solve the constrained nonlinear system. In order to guarantee global convergence, a robust loss function is chosen as the merit function, and the projected gradient method inserted is used to decrease the merit function. This algorithm is suitable for handling large-scale problems and possesses superlinear convergence rate. The global convergence of this algorithm is proved and the convergence rate is analyzed. The detailed implementation is discussed, and some numerical tests for solving large-scale semi-infinite programming problems, with examples up to 2000 decision variables, are reported.
URI: http://hdl.handle.net/10397/4764
ISSN: 1052-6234
EISSN: 1095-7189
DOI: 10.1137/040619867
Rights: © 2006 Society for Industrial and Applied Mathematics
Appears in Collections:Journal/Magazine Article

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