Abstract
In this paper bearing the same title as our earlier survey-paper [11] we pursue the goal of characterizing the global solutions of an optimization problem, i.e. getting at necessary and sufficient conditions for a feasible point to be a global minimizer (or maximizer) of the objective function. We emphasize nonconvex optimization problems presenting some specific structures like ‘convex-anticonvex’ ones or quadratic ones.
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Hiriart-Urruty, JB. Conditions for Global Optimality 2. Journal of Global Optimization 13, 349–367 (1998). https://doi.org/10.1023/A:1008365206132
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DOI: https://doi.org/10.1023/A:1008365206132