QUADRATIC APPROXIMATIONS IN CONVEX NONDIFFERENTIABLE OPTIMIZATION

被引：7
作者：
GAUDIOSO, M
MONACO, MF
机构：
[1] Univ della Calabria, Calabria
来源：
SIAM JOURNAL ON CONTROL AND OPTIMIZATION | 1991年 / 29卷 / 01期
关键词：
NONDIFFERENTIABLE OPTIMIZATION; BUNDLE METHODS;
D O I：
10.1137/0329003
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
An implementable descent method for the unconstrained minimization of convex nonsmooth functions of several variables is described. The algorithm is characterized by the use of a set of quadratic approximations of the objective function in order to compute the search direction. The resulting direction finding subproblem is shown to be equivalent to a structural parametric quadratic programming problem. The convergence of the algorithm to the minimum is proved, and numerical experience is reported.
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页码：58 / 70
页数：13
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