Abstract and Applied Analysis

A Novel Optimization Method for Nonconvex Quadratically Constrained Quadratic Programs

Hongwei Jiao, Yong-Qiang Chen, and Wei-Xin Cheng

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Abstract

This paper presents a novel optimization method for effectively solving nonconvex quadratically constrained quadratic programs (NQCQP) problem. By applying a novel parametric linearizing approach, the initial NQCQP problem and its subproblems can be transformed into a sequence of parametric linear programs relaxation problems. To enhance the computational efficiency of the presented algorithm, a cutting down approach is combined in the branch and bound algorithm. By computing a series of parametric linear programs problems, the presented algorithm converges to the global optimum point of the NQCQP problem. At last, numerical experiments demonstrate the performance and computational superiority of the presented algorithm.

Article information

Source
Abstr. Appl. Anal., Volume 2014, Special Issue (2014), Article ID 698489, 11 pages.

Dates
First available in Project Euclid: 2 October 2014

Permanent link to this document
https://projecteuclid.org/euclid.aaa/1412278788

Digital Object Identifier
doi:10.1155/2014/698489

Mathematical Reviews number (MathSciNet)
MR3206814

Zentralblatt MATH identifier
07022906

Citation

Jiao, Hongwei; Chen, Yong-Qiang; Cheng, Wei-Xin. A Novel Optimization Method for Nonconvex Quadratically Constrained Quadratic Programs. Abstr. Appl. Anal. 2014, Special Issue (2014), Article ID 698489, 11 pages. doi:10.1155/2014/698489. https://projecteuclid.org/euclid.aaa/1412278788


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