An improved lower bound and approximation algorithm for binary constrained quadratic programming problem

This paper presents an improved lower bound and an approximation algorithm based on spectral decomposition for the binary constrained quadratic programming problem. To decompose spectrally the quadratic matrix in the objective function, we construct a low rank problem that provides a lower bound. Th...

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Veröffentlicht in:Journal of global optimization Jg. 48; H. 3; S. 497 - 508
Hauptverfasser: Lu, Cheng, Wang, Zhenbo, Xing, Wenxun
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Boston Springer US 01.11.2010
Schlagworte:
Computer Science
Mathematics
Mathematics and Statistics
Operations Research/Decision Theory
Optimization
Real Functions
Lower bound
Quadratic integer programming
Spectral decomposition
Approximation algorithm
ISSN:0925-5001, 1573-2916
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Zusammenfassung:This paper presents an improved lower bound and an approximation algorithm based on spectral decomposition for the binary constrained quadratic programming problem. To decompose spectrally the quadratic matrix in the objective function, we construct a low rank problem that provides a lower bound. Then an approximation algorithm for the binary quadratic programming problem together with a worst case performance analysis for the algorithm is provided.
ISSN:0925-5001
1573-2916
DOI:10.1007/s10898-009-9504-1