On computing the mordukhovich subdifferential using directed sets in two dimensions

Robert Baier, Elza Farkhi, Vera Roshchina

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

11 Scopus citations

Abstract

The Mordukhovich subdifferential, being highly important in variational and nonsmooth analysis and optimization, often happens to be hard to calculate.We propose a method for computing the Mordukhovich subdifferential of differences of sublinear (DS) functions via the directed subdifferential of differences of convex (DC) functions. We restrict ourselves to the two-dimensional case mainly for simplicity of the proofs and for the visualizations. The equivalence of the Mordukhovich symmetric subdifferential (the union of the corresponding subdifferential and superdifferential) to the Rubinov subdifferential (the visualization of the directed subdifferential) is established for DS functions in two dimensions. The Mordukhovich subdifferential and superdifferential are identified as parts of the Rubinov subdifferential. In addition, it is possible to construct the directed subdifferential in a way similar to the Mordukhovich one by considering outer limits of Fréchet subdifferentials. The results are extended to the case of DC functions. Examples illustrating the obtained results are presented.

Original languageEnglish
Title of host publicationSpringer Optimization and Its Applications
PublisherSpringer International Publishing
Pages59-93
Number of pages35
DOIs
StatePublished - 2010

Publication series

NameSpringer Optimization and Its Applications
Volume47
ISSN (Print)1931-6828
ISSN (Electronic)1931-6836

Funding

FundersFunder number
Hermann Minkowski Center for Geometry
Tel Aviv University

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