A Rank-Two Feasible Direction Algorithm for the Binary Quadratic Programming

Based on the semidefinite programming relaxation of the binary quadratic programming, a rank-two feasible direction algorithm is presented. The proposed algorithm restricts the rank of matrix variable to be two in the semidefinite programming relaxation and yields a quadratic objective function with...

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Main Authors: Xuewen Mu, Yaling Zhang
Format: Article
Language:English
Published: Wiley 2013-01-01
Series:Journal of Applied Mathematics
Online Access:http://dx.doi.org/10.1155/2013/963563
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author Xuewen Mu
Yaling Zhang
author_facet Xuewen Mu
Yaling Zhang
author_sort Xuewen Mu
collection DOAJ
description Based on the semidefinite programming relaxation of the binary quadratic programming, a rank-two feasible direction algorithm is presented. The proposed algorithm restricts the rank of matrix variable to be two in the semidefinite programming relaxation and yields a quadratic objective function with simple quadratic constraints. A feasible direction algorithm is used to solve the nonlinear programming. The convergent analysis and time complexity of the method is given. Coupled with randomized algorithm, a suboptimal solution is obtained for the binary quadratic programming. At last, we report some numerical examples to compare our algorithm with randomized algorithm based on the interior point method and the feasible direction algorithm on max-cut problem. Simulation results have shown that our method is faster than the other two methods.
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institution OA Journals
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publishDate 2013-01-01
publisher Wiley
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series Journal of Applied Mathematics
spelling doaj-art-69c4e44ad00f4ee2a73455d28fb2c06a2025-08-20T02:23:56ZengWileyJournal of Applied Mathematics1110-757X1687-00422013-01-01201310.1155/2013/963563963563A Rank-Two Feasible Direction Algorithm for the Binary Quadratic ProgrammingXuewen Mu0Yaling Zhang1School of Mathematics and Statistics, Xidian University, Xi’an 710071, ChinaSchool of Mathematics and Statistics, Xidian University, Xi’an 710071, ChinaBased on the semidefinite programming relaxation of the binary quadratic programming, a rank-two feasible direction algorithm is presented. The proposed algorithm restricts the rank of matrix variable to be two in the semidefinite programming relaxation and yields a quadratic objective function with simple quadratic constraints. A feasible direction algorithm is used to solve the nonlinear programming. The convergent analysis and time complexity of the method is given. Coupled with randomized algorithm, a suboptimal solution is obtained for the binary quadratic programming. At last, we report some numerical examples to compare our algorithm with randomized algorithm based on the interior point method and the feasible direction algorithm on max-cut problem. Simulation results have shown that our method is faster than the other two methods.http://dx.doi.org/10.1155/2013/963563
spellingShingle Xuewen Mu
Yaling Zhang
A Rank-Two Feasible Direction Algorithm for the Binary Quadratic Programming
Journal of Applied Mathematics
title A Rank-Two Feasible Direction Algorithm for the Binary Quadratic Programming
title_full A Rank-Two Feasible Direction Algorithm for the Binary Quadratic Programming
title_fullStr A Rank-Two Feasible Direction Algorithm for the Binary Quadratic Programming
title_full_unstemmed A Rank-Two Feasible Direction Algorithm for the Binary Quadratic Programming
title_short A Rank-Two Feasible Direction Algorithm for the Binary Quadratic Programming
title_sort rank two feasible direction algorithm for the binary quadratic programming
url http://dx.doi.org/10.1155/2013/963563
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AT yalingzhang aranktwofeasibledirectionalgorithmforthebinaryquadraticprogramming
AT xuewenmu ranktwofeasibledirectionalgorithmforthebinaryquadraticprogramming
AT yalingzhang ranktwofeasibledirectionalgorithmforthebinaryquadraticprogramming