RANDOM PERTURBATION OF THE PROJECTED VARIABLE METRIC METHOD FOR NONSMOOTH NONCONVEX OPTIMIZATION PROBLEMS WITH LINEAR CONSTRAINTS

被引：7

作者：

El Mouatasim, Abdelkrim ^{[1
,2
]}

Ellaia, Rachid ^{[2
]}

de Cursi, Eduardo Souza ^{[3
]}

机构：

[1] Jazan Univ, Dept Math, Fac Sci, Jazan, Saudi Arabia

[2] Mohammed V Agdal Univ, Lab Study & Res Appl Math, Mohammadia Sch Engineers, Rabat, Morocco

[3] Inst Natl Sci Appl, St Etienne, France

来源：

INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS AND COMPUTER SCIENCE | 2011年 / 21卷 / 02期

关键词：

global optimization; linear constraints; variable metric method; stochastic perturbation; nonsmooth optimization; MINIMIZATION; ALGORITHMS; CONVERGENCE;

D O I：

10.2478/v10006-011-0024-z

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We present a random perturbation of the projected variable metric method for solving linearly constrained nonsmooth (i.e., nondifferentiable) nonconvex optimization problems, and we establish the convergence to a global minimum for a locally Lipschitz continuous objective function which may be nondifferentiable on a countable set of points. Numerical results show the effectiveness of the proposed approach.

引用

页码：317 / 329

页数：13

共 34 条

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[Anonymous], 1993, CONVEX ANAL MINIMIZA

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