Nonlinear Optimization II
Theory and algorithms for nonlinearly constrained optimization. Relevant geometric concepts, including tangent and normal cones, theorems of the alternative, and separation results. Constraint qualifications. Geometric and algebraic expression of first-order optimality conditions. Second-order optimality conditions. Duality. Nonlinear programming algorithms: merit functions and filters; interior-point, augmented Lagrangian, and sequential quadratic programming algorithms.
Summary
Recent recorded grades — Spring 2020: 3.71 GPA, 83.3% A/AB (n=12 letter grades); Fall 2022: 3.59 GPA, 76.5% A/AB (n=17 letter grades); Spring 2026: 3.59 GPA, 72.7% A/AB (n=11 letter grades).
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