A sequential cutting plane algorithm for solving convex NLP problems

In this paper we look at a new algorithm for solving convex nonlinear programming optimization problems. The algorithm is a cutting plane-based method, where the sizes of the subproblems remain fixed, thus avoiding the issue with constantly growing subproblems we have for the classical Kelley’s cutt...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	European journal of operational research Jg. 173; H. 2; S. 444 - 464
Hauptverfasser:	Still, Claus, Westerlund, Tapio
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier B.V 01.09.2006 Elsevier Elsevier Sequoia S.A
Schriftenreihe:	European Journal of Operational Research
Schlagworte:	Algorithms Applied sciences Convex programming Cutting plane algorithms Exact sciences and technology Nonlinear programming Operational research and scientific management Operational research. Management science Operations research Optimization techniques Sequential linear programming Studies Cutting plane algorithms Nonlinear programming Convex programming Sequential linear programming Sequential method Linear programming Numerical method Non linear programming Cutting plane method Competitive algorithms
ISSN:	0377-2217, 1872-6860
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!