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zbMATH Open
Article . 1993
Data sources: zbMATH Open
Mathematics of Operations Research
Article . 1993 . Peer-reviewed
Data sources: Crossref
DBLP
Article . 1993
Data sources: DBLP
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Semiregularity and Generalized Subdifferentials with Applications to Optimization

Semiregularity and generalized subdifferentials with applications to optimization
Authors: John R. Birge; Liqun Qi 0001;

Semiregularity and Generalized Subdifferentials with Applications to Optimization

Abstract

The Michel-Penot subdifferential of a locally Lipschitzian function is the principal part of the Clarke subdifferential. It coincides with the G-derivative at differentiable points. A locally Lipschitzian function can be determined by its Michel-Penot subdifferential uniquely up to an additive constant, though this cannot be done by its Clarke subdifferential if the set of abnormal points is not negligible. A set-valued operator is the Michel-Penot subdifferential of a locally Lipschitzian function if and only if it is a seminormal operator satisfying a cyclical condition. Various calculus rules hold for the Michel-Penot subdifferential. Equalities hold for these rules at a point under semiregularity, which is weaker than regularity. For a locally Lipschitzian function in a separable Banach space, semiregularity holds everywhere except for a Haar zero set. Applications in optimization are discussed.

Related Organizations
Keywords

nonsmooth analysis, Lipschitz (Hölder) classes, locally Lipschitzian function, Nonsmooth analysis, semiregularity, Clarke subdifferential, Michel-Penot subdifferential

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
24
Top 10%
Top 10%
Average
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