A Global Optimization Algorithm for Generalized Quadratic Programming

We present a global optimization algorithm for solving generalized quadratic programming (GQP), that is, nonconvex quadratic programming with nonconvex quadratic constraints. By utilizing a new linearizing technique, the initial nonconvex programming problem (GQP) is reduced to a sequence of relaxat...

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Main Authors: Hongwei Jiao, Yongqiang Chen
Format: Article
Language:English
Published: Wiley 2013-01-01
Series:Journal of Applied Mathematics
Online Access:http://dx.doi.org/10.1155/2013/215312
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author Hongwei Jiao
Yongqiang Chen
author_facet Hongwei Jiao
Yongqiang Chen
author_sort Hongwei Jiao
collection DOAJ
description We present a global optimization algorithm for solving generalized quadratic programming (GQP), that is, nonconvex quadratic programming with nonconvex quadratic constraints. By utilizing a new linearizing technique, the initial nonconvex programming problem (GQP) is reduced to a sequence of relaxation linear programming problems. To improve the computational efficiency of the algorithm, a range reduction technique is employed in the branch and bound procedure. The proposed algorithm is convergent to the global minimum of the (GQP) by means of the subsequent solutions of a series of relaxation linear programming problems. Finally, numerical results show the robustness and effectiveness of the proposed algorithm.
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institution Kabale University
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publishDate 2013-01-01
publisher Wiley
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series Journal of Applied Mathematics
spelling doaj-art-bd7141f725f648e4ba0fbe2ce4a5f0d72025-02-03T05:58:20ZengWileyJournal of Applied Mathematics1110-757X1687-00422013-01-01201310.1155/2013/215312215312A Global Optimization Algorithm for Generalized Quadratic ProgrammingHongwei Jiao0Yongqiang Chen1Department of Mathematics, Henan Institute of Science and Technology, Xinxiang 453003, ChinaDepartment of Mathematics, Henan Normal University, Xinxiang 453007, ChinaWe present a global optimization algorithm for solving generalized quadratic programming (GQP), that is, nonconvex quadratic programming with nonconvex quadratic constraints. By utilizing a new linearizing technique, the initial nonconvex programming problem (GQP) is reduced to a sequence of relaxation linear programming problems. To improve the computational efficiency of the algorithm, a range reduction technique is employed in the branch and bound procedure. The proposed algorithm is convergent to the global minimum of the (GQP) by means of the subsequent solutions of a series of relaxation linear programming problems. Finally, numerical results show the robustness and effectiveness of the proposed algorithm.http://dx.doi.org/10.1155/2013/215312
spellingShingle Hongwei Jiao
Yongqiang Chen
A Global Optimization Algorithm for Generalized Quadratic Programming
Journal of Applied Mathematics
title A Global Optimization Algorithm for Generalized Quadratic Programming
title_full A Global Optimization Algorithm for Generalized Quadratic Programming
title_fullStr A Global Optimization Algorithm for Generalized Quadratic Programming
title_full_unstemmed A Global Optimization Algorithm for Generalized Quadratic Programming
title_short A Global Optimization Algorithm for Generalized Quadratic Programming
title_sort global optimization algorithm for generalized quadratic programming
url http://dx.doi.org/10.1155/2013/215312
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