New variable-metric algorithms for nondifferentiable optimization problems

Uryasev, S. (1991). New variable-metric algorithms for nondifferentiable optimization problems. Journal of Optimization Theory and Applications 71 (2) 359-388. 10.1007/BF00939925.

Full text not available from this repository.

Abstract

This paper deals with new variable-metric algorithms for nonsmooth optimization problems, the so-called adaptive algorithms. The essence of these algorithms is that there are two simultaneously working gradient algorithms: the first is in the main space and the second is in the space of the matrices that modify the main variables. The convergence of these algorithms is proved for different cases. The results of numerical experiments are also given.

Item Type:	Article
Research Programs:	Social & Environmental Dimensions of Technology (SET)
Depositing User:	Romeo Molina
Date Deposited:	21 Apr 2016 14:15
Last Modified:	27 Aug 2021 17:40
URI:	https://pure.iiasa.ac.at/12876

Actions (login required)

View Item