Linear Programming and Quadratic Programming

Giorgio Giorgi (), Bienvenido Jiménez () and Vicente Novo ()
Additional contact information
Giorgio Giorgi: University of Pavia
Bienvenido Jiménez: National University of Distance Education
Vicente Novo: National University of Distance Education

Chapter Chapter 9 in Basic Mathematical Programming Theory, 2023, pp 275-316 from Springer

Abstract: Abstract As said in the previous pages, a Linear Programming problem (L. P. for friends)Problemlinear programming is characterized by a linear (or a linear affine) objective function and by linear (or linear affine) constraints. Usually, the variables are also required to be nonnegative. As L. P. is a particular case of nonlinear programming (the involved functions are both convex and concave and differentiable on $$\mathbb {R}^n$$ R n ), all theorems seen for the general case of nonlinear programming hold also for L. P. and almost always in a simplified form.

Date: 2023
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:isochp:978-3-031-30324-1_9

Ordering information: This item can be ordered from
http://www.springer.com/9783031303241

DOI: 10.1007/978-3-031-30324-1_9

Access Statistics for this chapter

More chapters in International Series in Operations Research & Management Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().