Convex composite minimization with C1,1functions

V. Jeyakumar; Xiaoqi Yang

doi:10.1007/BF02192162

Convex composite minimization with C^1,1functions

V. Jeyakumar
, Xiaoqi Yang

Research output: Journal article publication › Journal article › Academic research › peer-review

19 Citations (Scopus)

Abstract

In this paper, we present second-order optimality conditions for convex composite minimization problems in which the objective function is a composition of a finite-valued or a nonfinite-valued lower semicontinuous convex function and a C1,1function. The results provide optimality conditions for composite problems under reduced differentiability requirements.

Original language	English
Pages (from-to)	631-648
Number of pages	18
Journal	Journal of Optimization Theory and Applications
Volume	86
Issue number	3
DOIs	https://doi.org/10.1007/BF02192162
Publication status	Published - 1 Sept 1995
Externally published	Yes

Keywords

basic constraint qualifications
Convex composite minimization problems
generalized second-order directional derivatives
generalized Taylor expansions
second-order optimality conditions

ASJC Scopus subject areas

Control and Optimization
Management Science and Operations Research
Applied Mathematics

More information

10.1007/BF02192162

Cite this

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AB - In this paper, we present second-order optimality conditions for convex composite minimization problems in which the objective function is a composition of a finite-valued or a nonfinite-valued lower semicontinuous convex function and a C1,1function. The results provide optimality conditions for composite problems under reduced differentiability requirements.

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KW - Convex composite minimization problems

KW - generalized second-order directional derivatives

KW - generalized Taylor expansions

KW - second-order optimality conditions

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