Mini lecture: Introduction to Mathematical Optimization (IOPTI) - M. Stingl

Beginning: 9 am

Introduction to Mathematical Optimization (IOPTI)
Classification: Mathematical skills (A), general background
Lecturer: Michael Stingl
Language: English
Contents:

* Unconstrained and Constrained Optimisation problems
* Necessary and sufficient Optimality conditions
* Descent methods – generic framework and Newton’s method
* Lagrange-Duality and Karush-Kuhn-Tucker (KKT) conditions
* Lagrange-Newton method for equality constrained optimization
* Basics of interior point (IP) as well as sequential quadratic programming (SQP) idea

Objectives:
The students

* are to model and classify finite dimensional optimization problems
* to derive optimality conditions for various classes of optimization problems
* to apply and implement descent-based solution strategies including Newton’s method for unconstrained optimization
* calculate solutions of constrained optimization problems based on KKT conditions
* know to apply advanced optimization techniques like IP or SQP to the local solution of constrained smooth non-linear optimization problems