Basic knowledge of Algorithms and Data Structures (e.g., Informatik III at University of Augsburg)
Online/Digitale Veranstaltung
Veranstaltung wird online/digital abgehalten.
Hauptunterrichtssprache
englisch
Literaturhinweise
David P. Williamson and David B. Shmoys, The Design of Approximation Algorithms, Cambridge University Press.
Vijay V. Vazirani, Approximation Algorithms, Springer.
Given an NP-hard optimization problem, how well can it be approximated in polynomial time? It is exciting and challenging to understand the approximability of fundamental optimization problems. This course mainly focuses on upper bounds, i.e., designing efficient approximation algorithms.
In this course, we will study several classes of problems, such as packing problems, network design, and graph problems. We will cover central algorithmic techniques for designing approximation algorithms, including greedy algorithms, dynamic programming, linear and semi-definite programming, and randomization.
This course does not require specific prerequisite, other than basic knowledge in algorithms and in data structures.