A deterministic global optimization algorithm based on a linearizing method for nonconvex quadratically constrained programs

Authors:
Shao-Jian Qu;Ying Ji;Ke-Cun Zhang
Affiliations:
Harbin Institute of Technology, Harbin 150080, China;Faculty of Science, Xi'an Jiaotong University, Xi'an 710049, China;Faculty of Science, Xi'an Jiaotong University, Xi'an 710049, China
Venue:
Mathematical and Computer Modelling: An International Journal
Year:
2008

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Abstract

In this paper a deterministic global optimization algorithm for solving nonconvex quadratically constrained quadratic programs (NQP) is proposed. Utilizing a new linearizing method, the initial nonlinear and nonconvex NQP problem is reduced to a sequence of linear programming problems. The proposed algorithm is proven to be convergent to the global minimum through the solutions of a series of linear programming problems. Several NQP examples in the literatures are tested to demonstrate that the proposed method can systematically solve these examples to find the global optimum within a prespecified error.