EconPapers    
Economics at your fingertips  
 

Conjugate Gradient Methods Memoryless BFGS Preconditioned

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

Chapter Chapter 8 in Nonlinear Conjugate Gradient Methods for Unconstrained Optimization, 2020, pp 249-309 from Springer

Abstract: Abstract Conjugate gradient methods are widely acknowledged to be among the most efficient and robust methods for solving the large-scale unconstrained nonlinear optimization problems

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_8

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

DOI: 10.1007/978-3-030-42950-8_8

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 ().

 
Page updated 2025-04-01
Handle: RePEc:spr:spochp:978-3-030-42950-8_8