Recent Developments in Algorithms and Software for Trust Region Methods

J. J. Moré
Additional contact information
J. J. Moré: Argonne Nat. Lab., Mathematics and Computer Science Division

A chapter in Mathematical Programming The State of the Art, 1983, pp 258-287 from Springer

Abstract: Abstract Trust region methods are an important class of iterative methods for the solution of nonlinear optimization problems. Algorithms in this class have been proposed for the solution of systems of nonlinear equations, nonlinear estimation problems, unconstrained and constrained optimization, nondifferentiable optimization, and large scale optimization. Interest in trust region methods derives, in part, from the availability of strong convergence results and from the development of software for these methods which is reliable, efficient, and amazingly free of ad-hoc decisions. In this paper we survey the theoretical and practical results available for trust region methods and discuss the relevance of these results to the implementation of trust region methods.

Keywords: Conjugate Gradient; Conjugate Gradient Method; Trust Region; Trust Region Method; Unconstrained Minimization (search for similar items in EconPapers)
Date: 1983
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:978-3-642-68874-4_11

Ordering information: This item can be ordered from
http://www.springer.com/9783642688744

DOI: 10.1007/978-3-642-68874-4_11

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 ().