Optimality Conditions
Adil Bagirov (),
Napsu Karmitsa () and
Marko M. Mäkelä ()
Additional contact information
Adil Bagirov: School of Information Technology and Mathematical Sciences, University of Ballarat
Napsu Karmitsa: University of Turku
Marko M. Mäkelä: University of Turku
Chapter Chapter 4 in Introduction to Nonsmooth Optimization, 2014, pp 117-137 from Springer
Abstract:
Abstract We present some results connecting the theories of nonsmooth analysis and optimization. We first define global and local minima of functions. After that, we generalize the classical first order optimality conditions for unconstrained nonsmooth optimization. Furthermore, we define linearizations for locally Lipschitz continuous functions by using subgradient information, and present their basic properties. These linearizations are suitable for function approximation. Finally, we define the notion of a descent direction and show how to find it for a locally Lipschitz continuous function.
Keywords: Unconstrained Nonsmooth Optimization; Subgradient Information; Descent Direction; Geometrical Optimality Condition; Nonsmooth Analysis (search for similar items in EconPapers)
Date: 2014
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-08114-4_4
Ordering information: This item can be ordered from
http://www.springer.com/9783319081144
DOI: 10.1007/978-3-319-08114-4_4
Access Statistics for this chapter
More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().