Webrelaunch 2020

Probability Theory and Combinatorial Optimization (Sommersemester 2020)

  • Dozent*in: Prof. Dr. Daniel Hug
  • Veranstaltungen: Vorlesung (0160000), Übung (0160010)
  • Semesterwochenstunden: 4+2

All materials and further information concerning the course will be provided in the ILIAS platform.

Vorlesung: Mittwoch 11:30-13:00 SR 2.058
Donnerstag 9:45-11:15 SR 3.061
Übung: Montag 15:45-17:15 SR 3.069 Beginn: 27.4.2020
Dozent, Übungsleiter Prof. Dr. Daniel Hug
Sprechstunde: Nach Vereinbarung.
Zimmer 2.051 Kollegiengebäude Mathematik (20.30)
Email: daniel.hug@kit.edu
Dozentin Sekretariatsdaten
Zimmer 2.056 und 2.002 Kollegiengebäude Mathematik (20.30)
Übungsleiter Dr. Moritz Otto
Sprechstunde: nach Vereinbarung
Zimmer 2.005 Kollegiengebäude Mathematik (20.30)
Email: moritz.otto@kit.edu

Course Description

This course is devoted to the analysis of algorithms and combinatorial optimization problems in a probabilistic framework. A natural setting for the investigation of such problems is often provided by a (geometric) graph. For a given system (graph), the average or most likely behavior of an objective function of the system will be studied. In addition to asymptotic results, which describe a system as its size increases, quantitative laws for systems of fixed size will be described. Among the specific problems to be explored are

  • the long-common-subsequence problem,
  • packing problems,
  • the Euclidean traveling salesman problem,
  • minimal Euclidean matching,
  • minimal Euclidean spanning tree.

For the analysis of problems of this type, several techniques and concepts have been developed and will be introduced and applied in this course. Some of these are

  • concentration inequalities and concentration of measure,
  • subadditivity and superadditivity,
  • martingale methods,
  • isoperimetry,
  • entropy.

Course Notes will be made available in English in the Ilias platform.

Prerequisites: Probability Theory

Exercises: Exercises and their solutions will be available in the Ilias platform.


Oral examination (30 minutes) by appointment


  • Boucheron, S., Lugosi, G., Massart, P. Concentration Inequalities, Oxford University Press, Oxford, 2013.
  • Dubhashi, D., Panconesi, A. Concentration of Measure for the Analysis of Randomized Algorithms, Cambridge University Press, Cambridge, 2009.
  • Ledoux, M. The Concentration of Measure Phenomenon. American Mathematical Society, vol. 89, 2001.
  • Steele, J.M. Probability Theory and Combinatorial Optimization. SIAM, 1997.
  • Yukich, J.E. Probability Theory of Classical Euclidean Optimization Problems. Lecture Notes in Mathematics, Vol. 1675, Springer, Berlin, 1998.
  • Vershynin, R. High-dimensional probability. An Introduction with Applications in Data Science. Cambridge University Press. 2018.