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A new accelerating method for global non-convex quadratic optimization with non-convex quadratic constraints. (English) Zbl 1141.65048

The authors investigate an extension to the algorithm proposed by S.-J. Qu, K.-C. Zhang and Y. Ji [Appl. Math. Comput. 186, No. 1, 763-771 (2007; Zbl 1116.65070)] to produce a novel accelerating global optimization algorithm for non-convex quadratic problems with non-convex quadratic constraints. The paper begins with a brief introduction to this problem, followed by the presentation of the new deleting technique used for eliminating a region where the global optimum solution does not exist. This technique is then incorporated in the proposed algorithm, which is presented in Section 3, and its convergence properties are studied in detail. The last section presents the results of the numerical experimentation using the proposed algorithm. The article concludes with a section containing a summary of the main contributions of this paper and a list of useful relevant references.

MSC:

65K05 Numerical mathematical programming methods
90C20 Quadratic programming
90C26 Nonconvex programming, global optimization
90C57 Polyhedral combinatorics, branch-and-bound, branch-and-cut

Citations:

Zbl 1116.65070
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Full Text: DOI

References:

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This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.