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Globally Convergent Variable Metric Method for Convex Nonsmooth Unconstrained Minimization1

Globally Convergent Variable Metric Method for Convex Nonsmooth Unconstrained Minimization1

JournalJournal of Optimization Theory and Applications
PublisherSpringer Netherlands
ISSN0022-3239 (Print) 1573-2878 (Online)
IssueVolume 102, Number 3 / September, 1999
DOI10.1023/A:1022650107080
Pages593-613
Subject CollectionMathematics and Statistics
SpringerLink DateSaturday, October 30, 2004
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Globally Convergent Variable Metric Method for Convex Nonsmooth Unconstrained Minimization1

L. Lukscaronan1 and J. Vlccaronek1

(1) Institute of Computer Science, Academy of Sciences of the Czech Republic, Prague, Czech Republic

Abstract  A special variable metric method is given for finding minima of convex functions that are not necessarily differentiable. Time-consuming quadratic programming subproblems do not need to be solved. Global convergence of the method is established. Some encouraging numerical experience is reported.

Nonsmooth minimization - convex minimization - numerical methods - variable metric methods - global convergence

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