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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