CONVERGENCE OF SOME ALGORITHMS FOR CONVEX MINIMIZATION

被引：178

作者：

CORREA, R

LEMARECHAL, C

机构：

[1] UNIV CHILE, DEPT MATH, SANTIAGO, CHILE

[2] INRIA, LE CHESNAY, FRANCE

来源：

MATHEMATICAL PROGRAMMING | 1993年 / 62卷 / 02期

关键词：

NONDIFFERENTIABLE OPTIMIZATION; CONVEX PROGRAMMING; PROXIMAL POINT METHOD; BUNDLE ALGORITHMS; GLOBAL CONVERGENCE;

D O I：

10.1007/BF01585170

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

We present a simple and unified technique to establish convergence of various minimization methods. These contain the (conceptual) proximal point method, as well as implementable forms such as bundle algorithms, including the classical subgradient relaxation algorithm with divergent series.

引用

页码：261 / 275

页数：15

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AUSLENDER A, 1987, MATH PROGRAM STUD, V30, P102, DOI 10.1007/BFb0121157

[2]

BELLMAN RE, 1966, NUMERICAL INVERSION, P143

[3]

Cheney E.W., 1959, NUMER MATH, V1, P253

[4] A DESCENT ALGORITHM FOR NONSMOOTH CONVEX-OPTIMIZATION [J].