Other Conjugate Gradient Methods

Neculai Andrei ()
Additional contact information
Neculai Andrei: Academy of Romanian Scientists

Chapter Chapter 11 in Nonlinear Conjugate Gradient Methods for Unconstrained Optimization, 2020, pp 361-414 from Springer

Abstract: Abstract As already seen, the conjugate gradient algorithms presented so far use some principles based on: hybridization or modifications of the standard schemes, the memoryless or the scaled memoryless BFGS preconditioned or the three-term concept. The corresponding conjugate gradient algorithms are defined by the descent condition, the “pure” conjugacy or the Dai–Liao conjugacy conditions or by the minimization of the quadratic approximation with one or two parameters of the objective function. There are a number of convergence results, mainly based on the Zoutendijk and on the Nocedal conditions under the Wolfe line search (Dai, 2011). These algorithms have good numerical performances, being able to solve large-scale unconstrained optimization problems and applications. However, in the frame of conjugate gradient methods, which is a very active area of research, some other computational schemes were introduced in order to improve their numerical performances. They are too numerous to be presented in this study. However, a short description of some of them is as follows.

Date: 2020
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:spochp:978-3-030-42950-8_11

Ordering information: This item can be ordered from
http://www.springer.com/9783030429508

DOI: 10.1007/978-3-030-42950-8_11

Access Statistics for this chapter

More chapters in Springer Optimization and Its Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().