A new upper bound for the 0-1 quadratic knapsack problem

The 0-1 quadratic knapsack problem (QKP) consists in maximizing a positive quadratic pseudo-Boolean function subject to a linear capacity constraint. We present in this paper a new method, based on Lagrangian decomposition, for computing an upper bound of QKP. We report computational experiments whi...

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Veröffentlicht in:European journal of operational research Jg. 112; H. 3; S. 664 - 672
Hauptverfasser: Billionnet, Alain, Faye, Alain, Soutif, Éric
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Amsterdam Elsevier B.V 01.02.1999
Elsevier
Elsevier Sequoia S.A
Schriftenreihe:European Journal of Operational Research
Schlagworte:
0-1 Quadratic knapsack problem
Applied sciences
Bounds
Computational Complexity
Computational experiments
Computer Science
Exact sciences and technology
Flows in networks. Combinatorial problems
Knapsack problem
Lagrangian decomposition
Mathematical models
Operational research and scientific management
Operational research. Management science
Operations research
Optimization techniques
Quadratic programming
Studies
Theory
Lagrangian decomposition
Computational experiments
0-1 Quadratic knapsack problem
Quadratic programming
Bounds
Upper bound
Decomposition
Zero one programming
Lagrangian method
Knapsack problem
ISSN:0377-2217, 1872-6860
Online-Zugang:Volltext
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Zusammenfassung:The 0-1 quadratic knapsack problem (QKP) consists in maximizing a positive quadratic pseudo-Boolean function subject to a linear capacity constraint. We present in this paper a new method, based on Lagrangian decomposition, for computing an upper bound of QKP. We report computational experiments which demonstrate the sharpness of the bound (relative error very often less than 1%) for large size instances (up to 500 variables).
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
content type line 14
ISSN:0377-2217
1872-6860
DOI:10.1016/S0377-2217(97)00414-1