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

DOI10.1007/s11590-014-0768-0zbMath1317.90227OpenAlexW2147198066MaRDI QIDQ2018868

Cheng Lu, Xiao-ling Guo

Publication date: 25 March 2015

Published in: Optimization Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11590-014-0768-0

zbMATH Keywords

branch-and-boundlower boundsbinary quadratic programmingconvex reformulation

Mathematics Subject Classification ID

Quadratic programming (90C20) Boolean programming (90C09)

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Cites Work

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• On duality gap in binary quadratic programming
• An improved lower bound and approximation algorithm for binary constrained quadratic programming problem
• Using a mixed integer quadratic programming solver for the unconstrained quadratic \(0-1\) problem
• New bounds on the unconstrained quadratic integer programming problem
• Semidefinite programming versus the reformulation-linearization technique for nonconvex quadratically constrained quadratic programming
• Lattice preconditioning for the real relaxation branch-and-bound approach for integer least squares problems
• On the copositive representation of binary and continuous nonconvex quadratic programs
• On the gap between the quadratic integer programming problem and its semidefinite relaxation
• Computational aspects of a branch and bound algorithm for quadratic zero- one programming
• Improved approximation algorithms for maximum cut and satisfiability problems using semidefinite programming
• Convex Relaxations of (0, 1)-Quadratic Programming
• Semidefinite Programming
• Quasi-maximum-likelihood multiuser detection using semi-definite relaxation with application to synchronous CDMA