A note on the convergence of subgradient optimization methods

1 January 1983

journal article
research article
Published by Taylor & Francis in Mathematische Operationsforschung und Statistik. Series Optimization

Vol. 14 (4) , 537-541
https://doi.org/10.1080/02331938308842889

Abstract

The problem to minimize a convex function f over a closed convex set C on which it is subdifferentiable can be approached by methods of subgradient optimization. In this note, a simple condition is given under which a sequence generated by such a method is convergent if arid only if f attains its infimum over G. An answer to the question when this condition can be satisfied is given, too.

Keywords

CONVERGENT
SUBGRADIENT OPTIMIZATION METHODS
ATTAINS
CONVEX FUNCTION
SIMPLE CONDITION
CONVEX SET
CLOSED CONVEX

This publication has 2 references indexed in Scilit:

Monotone Operators and the Proximal Point Algorithm
SIAM Journal on Control and Optimization, 1976
Convex Analysis
Published by Walter de Gruyter GmbH ,1970