Journal of Applied Mathematics
- J. Appl. Math.
- Volume 2013 (2013), Article ID 215312, 9 pages.
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 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.
J. Appl. Math., Volume 2013 (2013), Article ID 215312, 9 pages.
First available in Project Euclid: 14 March 2014
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Jiao, Hongwei; Chen, Yongqiang. A Global Optimization Algorithm for Generalized Quadratic Programming. J. Appl. Math. 2013 (2013), Article ID 215312, 9 pages. doi:10.1155/2013/215312. https://projecteuclid.org/euclid.jam/1394808167