Target Audience: Master EI and MSCE
Next Exam: tbd (no responsibility is taken for the correctness of this information)
Additional Information: TUMonline
|Wednesday||13:15 – 14:45||Online|
|Friday||11:30 – 13:00||Online|
|First lecture: -|
Introduction: Problem Statement of Optimization, Basic Definitions, Categorization.
Convex Analysis: Convex Sets and Functions.
Linear Programming: Extremal points, Extremal directions.
Optimality Conditions: Karush-Kuhn-Tucker Conditions, Constraint Qualifications.
Lagrangian Duality: Duality Theorems, Solutions for the Primal and Dual Problem.
Algorithms: Subgradient Methods, Cutting Plane Algorithms, Projection Methods, Fixpoint Algorithms.
Applications: Network Optimization, Problems from Multiuser Information Theory, Resource Allocation, Parameter Optimization in Layered/Distributed Communication Systems.