Abstract
For the problem of maximizing a convex quadratic function under convex quadratic constraints, we derive conditions characterizing a globally optimal solution. The method consists in exploiting the global optimality conditions, expressed in terms of ∈-subdifferentials of convex functions and ∈-normal directions, to convex sets. By specializing the problem of maximizing a convex function over a convex set, we find explicit conditions for optimality.
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Hiriart-Urruty, JB. Global Optimality Conditions in Maximizing a Convex Quadratic Function under Convex Quadratic Constraints. Journal of Global Optimization 21, 443–453 (2001). https://doi.org/10.1023/A:1012752110010
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DOI: https://doi.org/10.1023/A:1012752110010