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Dissertation Defense |
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Committee: Dr. Yuri S. Ledyaev, Chair Date: Thursday, December 2, 2004 2:00 p.m. – 4:00 p.m. Abstract: We derive new first-order necessary and sufficient optimality conditions characterizing global minimizers in mathematical programming and optimal control problems. These conditions are based on level sets of an objective functional and they do not assume special structure of a problem (convexity, linearity, etc.). For a mathematical programming problem of minimization of a smooth functional on some compact convex set with equality nonlinear constraints, we derive first-order optimality conditions in the form of a generalized Lagrange multiplier rule. This rule should hold for any point from the level set of the objective functional corresponding to a global minimizer. We demonstrate that these necessary conditions become sufficient ones for optimality under additional assumption of non-degeneracy of the Lagrange multiplier rule.
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