Abstract
This paper presents a canonical dual approach for solving nonconvex quadratic programming problems subjected to both linear inequality constraints and box constrains. It is proved that the constrained nonconvex primal problem can be reformulated as a concave maximization dual problem with zero duality gap, which can be solved under certain conditions. Both global and local extremimality conditions are presented by the triality theory. Several applications are illustrated.
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The main result of this paper has been announced at the Seventh International Conference on Optimization: Techniques and Applications, Kobe, Japan, Dec. 12–15, 2007.
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Zhang, X., Zhu, J. & Gao, D.Y. Solution to nonconvex quadratic programming with both inequality and box constraints. Optim Eng 10, 183–191 (2009). https://doi.org/10.1007/s11081-008-9062-2
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DOI: https://doi.org/10.1007/s11081-008-9062-2