Hybrid Methods

Adil Bagirov (), Napsu Karmitsa () and Marko M. Mäkelä ()
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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 14 in Introduction to Nonsmooth Optimization, 2014, pp 313-325 from Springer

Abstract: Abstract In this chapter, we describe some methods that can be considered as hybrids of the classical nonsmooth optimization methods described before. The methods to be introduced are the variable metric bundle method and the quasi-secant method for solving general small- and medium-scale nonsmooth optimization problems; the modification of variable metric bundle method for solving large-scale nonsmooth optimization problems, that is, the limited memory bundle method; and the non-Euclidean restricted memory level method for extremely large-scale convex nonsmooth optimization problems.

Keywords: Limited Memory Bundle Method (LMBM); Null Step; Direction-finding Procedure; Aggregate Subgradient; Gradient Sampling Method (search for similar items in EconPapers)
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-08114-4_14

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DOI: 10.1007/978-3-319-08114-4_14

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