MATH 378 Nonlinear Optimization (3 credits)

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Offered by: Mathematics and Statistics (Faculty of Science)


Mathematics & Statistics (Sci) : Optimization terminology. Convexity. First- and second-order optimality conditions for unconstrained problems. Numerical methods for unconstrained optimization: Gradient methods, Newton-type methods, conjugate gradient methods, trust-region methods. Least squares problems (linear + nonlinear). Optimality conditions for smooth constrained optimization problems (KKT theory). Lagrangian duality. Augmented Lagrangian methods. Active-set method for quadratic programming. SQP methods.

Terms: Fall 2023

Instructors: Hoheisel, Tim (Fall)

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