Applied Graph Theory

Објавено: December 12, 2018

Course: Applied Graph Theory

Code: 3ФЕИТ08001

ECTS points: 6 ECTS

Number of classes per week: 3+0+0+3

Lecturer: Assoc. Prof. Dr. Vesna Andova

Course Goals (acquired competencies): After finishing this course, the students should deal with the basic concepts of classical graph theory and different models of random graphs.  They should learn and deal with different measures for large graphs (complex networks), and apply these measures in various real life networks.

Course Syllabus: Introduction to Graph Theory. Probability method: basic method, linearity of expectation, second moment. Erdos-Reny model for random graphs. Threshold function. Flow. Complex networks: small world, scale free networks, selfsimilar networks.   Centrality measures, vulnerability of networks, degree distribution and correlation, clustering coefficient, and other measures.   Dynamic of networks. Biological networks. Software Pajek. Fullerenes and nanotubes as graph structures.

Literature:

Required Literature

No.

Author

Title

Publisher

Year

1

A. Bondy, U.S.R. MurtyGraph TheorySpringer2008

2

M. NewmannNetworks: An IntroductionOxford University Press2010

3

E.EstradaThe Structure of  Complex NetworksOxford University Press2012

Additional Literature

No.

Author

Title

Publisher

Year

1

R. DistelGraph TheorySpringer-Verlag2010

2

U. Brandes, T. ErlebachNetwork Analysis: Methodological FoundationsSpringer2005