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Persistent URL http://purl.org/net/epubs/work/40546
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Record Id 40546
Title On the convergence of successive linear quadratic programming algorithms
Contributors
Abstract The global convergence properties of a class of penalty methods for nonlinear programming are analyzed. These methods include successive linear programming approaches, and more specifically, the successive linear-quadratic programming approach presented by Byrd, Gould, Nocedal and Waltz (Math. Programming 100(1):27{48, 2004). Every iteration requires the solution of two trust-region subproblems involving piecewise linear and quadratic models, respectively. It is shown that, for a xed penalty parameter, the sequence of iterates approaches stationarity of the penalty function. A procedure for dynamically adjusting the penalty parameter is described, and global convergence results for it are established.
Organisation CCLRC , ESC , CSE-NAG
Keywords
Funding Information
Related Research Object(s): 33858
Language English (EN)
Type Details URI(s) Local file(s) Year
Journal Article Sol Phys 16, no. 2 (2006): 471-489. doi:10.1137/S1052623403426532 2006
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