Optimization problems are ubiquitous in most scientific fields and engineering. The easiest such problems are linear and already have numerous applications. They are special cases of convex optimization problems, which are often efficiently solvable with many software implementations available. Many optimization problems are non-convex and are often hard to solve.
This seminar aims to provide a basic understanding of general principles of `easy' optimization problems (convex optimization). We will see selected examples for the theoretical analysis of standard algorithms for these problems. Then, we will also see example classes of non-convex optimization problems and heuristic ways to solve them. Throughout, there are opportunities to do numerical experiments with standard optimization packages as well as to look into examples for important applications.
Area classification:
Studiendekanat Elektrotechnik, Informatik und Mathematik
Stud.IP informationen about this course:
Home institute: Studiendekanat Elektrotechnik, Informatik und Mathematik (E)
Registered participants in Stud.IP: 4
Documents: 1
Supervised Theses
ongoing
2024
Ahmed, Taha (2024). Development of an iterative multi-agent coordination framework for congestion prevention in low voltage grids.
Busch, Marcel (2024). Entwicklung eines Netzmodells zur szenarienbasierten Untersuchung von Engpässen in heutigen und zukünftigen städtischen Verteilnetzen.
Lindner, Joost (2024). Entwicklung einer probabilistischen Lastprognose für die Niederspannungsebene elektrischer Verteilnetze.
Möller, Julius (2024). Untersuchung von Kennzahlen zur Bewertung der Diskriminierungsfreiheit von Engpassmanagementmaßnahmen.
Wilke, Jan Jakob (2024). Definition leistungsbasierter Netzregeln zur Engpassvermeidung in elektrischen Verteilnetzen.
completed
2024
Ming, Zhao (2024). Conceptual Design for a grid demonstrator for teaching purposes and development of a suitable distribution grid simulation.
2023
Kock am Brink, Jonas (2023). Entwicklung einer Engpassprognose für elektrische Verteilnetze mittels probabilistischer Verfahren.