Solution of boolean quadratic programming problems by two augmented Lagrangian algorithms based on a continuous relaxation

Many combinatorial optimization problems and engineering problems can be modeled as boolean quadratic programming (BQP) problems. In this paper, two augmented Lagrangian methods (ALM) are discussed for the solution of BQP problems based on a class of continuous functions. After convexification, the...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Journal of combinatorial optimization Jg. 39; H. 3; S. 792 - 825
Hauptverfasser:	Nayak, Rupaj Kumar, Mohanty, Nirmalya Kumar
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.04.2020 Springer Nature B.V
Schlagworte:	Algorithms Boolean Boolean algebra Combinatorial analysis Combinatorics Computing time Continuity (mathematics) Convex and Discrete Geometry Knapsack problem Lagrangian function Mathematical Modeling and Industrial Mathematics Mathematics Mathematics and Statistics Nonlinear programming Operations Research/Decision Theory Optimization Quadratic programming Theory of Computation Continuous relaxation Augmented Lagrangian method Max-cut problems Binary quadratic programming problem Image deconvolution QKP
ISSN:	1382-6905, 1573-2886
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!