Convex reformulation for binary quadratic programming problems via average objective value maximization

Quadratic convex reformulation is an important method for improving the performance of a branch-and-bound based binary quadratic programming solver. In this paper, we study a new convex reformulation method. By this reformulation, the efficiency of a branch-and-bound algorithm can be improved signif...

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Bibliographic Details

Published in:	Optimization letters Vol. 9; no. 3; pp. 523 - 535
Main Authors:	Lu, Cheng, Guo, Xiaoling
Format:	Journal Article
Language:	English
Published:	Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2015
Subjects:	Computational Intelligence Mathematics Mathematics and Statistics Numerical and Computational Physics Operations Research/Decision Theory Optimization Original Paper Simulation Lower bounds Branch-and-bound Binary quadratic programming Convex reformulation
ISSN:	1862-4472, 1862-4480
Online Access:	Get full text
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