Quadratic Programming and Nonlinear Optimization

Jean-Pierre Corriou
Additional contact information
Jean-Pierre Corriou: University of Lorraine

Chapter Chapter 11 in Numerical Methods and Optimization, 2021, pp 623-651 from Springer

Abstract: Abstract Quadratic programming strictly deals with the optimization of a quadratic function subject to linear constraints, but it is here extended to nonquadratic functions. The solution of QP is given by the simplex method but also using the barrier method. It is followed by the nonlinear optimization by successive quadratic programming. SQP is explained by different algorithms. Examples systematically illustrate the different techniques.

Date: 2021
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:978-3-030-89366-8_11

Ordering information: This item can be ordered from
http://www.springer.com/9783030893668

DOI: 10.1007/978-3-030-89366-8_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 ().