Parametric Lagrangian dual for the binary quadratic programming problem

Based on a difference between convex decomposition of the Lagrangian function, we propose and study a family of parametric Lagrangian dual for the binary quadratic program. Then we show they improve several lower bounds in recent literature.

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Bibliographic Details
Published in:Journal of global optimization Vol. 61; no. 2; pp. 221 - 233
Main Authors: Xia, Yong, Xing, Wenxun
Format: Journal Article
Language:English
Published: Boston Springer US 01.02.2015
Springer
Springer Nature B.V
Subjects:
Computer Science
Decomposition
Eigenvalues
Financial analysis
Laboratories
Lower bounds
Mathematical analysis
Mathematics
Mathematics and Statistics
Operations Research/Decision Theory
Optimization
Program development software
Quadratic programming
Real Functions
Software development
Studies
China
90C20
Lower bound
90C10
Binary quadratic program
Semidefinite programming
D.C. decomposition
Lagrangian dual
90C09
ISSN:0925-5001, 1573-2916
Online Access:Get full text
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Description
Summary:Based on a difference between convex decomposition of the Lagrangian function, we propose and study a family of parametric Lagrangian dual for the binary quadratic program. Then we show they improve several lower bounds in recent literature.
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ISSN:0925-5001
1573-2916
DOI:10.1007/s10898-014-0164-4