Course detail

Graph Algorithms (in English)

FIT-GALeAcad. year: 2023/2024

This course discusses graph representations and graphs algorithms for searching (depth-first search, breadth-first search), topological sorting, searching of graph components and strongly connected components, trees and minimal spanning trees, single-source and all-pairs shortest paths, maximal flows and minimal cuts, maximal bipartite matching, Euler graphs, and graph coloring. The principles and complexities of all presented algorithms are discussed.

Language of instruction

English

Number of ECTS credits

5

Mode of study

Not applicable.

Guarantor

prof. RNDr. Alexandr Meduna, CSc.

Department

Department of Information Systems (UIFS)

Offered to foreign students

Of all faculties

Entry knowledge

Foundations in discrete mathematics and algorithmic thinking.

Rules for evaluation and completion of the course

  • Mid-term exam - 15 points.
  • Projects - 25 points.
  • Final exam - 60 points. The minimal number of points which can be obtained from the final exam is 25. Otherwise, no points from the final exam will be assigned to a student.

 

Aims

Introduction to graph theory with focus on graph representations, graph algorithms and their complexities.
Fundamental ability to construct an algorithm for a graph problem and to analyze its time and space complexity.

Study aids

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Not applicable.

Recommended reading

Electronic copy of lectures. (EN)
J. Demel, Grafy, SNTL Praha, 1988. (CS)
T.H. Cormen, C.E. Leiserson, R.L. Rivest, C. Stein, Introduction to Algorithms, 3rd edition. MIT Press, 2009. (EN)
J. Demel, Grafy a jejich aplikace, Academia, 2002. (Více o knize) (CS)
J.A. McHugh, Algorithmic Graph Theory, Prentice-Hall, 1990. (EN)
K. Erciyes: Guide to Graph Algorithms (Sequential, Parallel and Distributed). Springer, 2018. (EN)

A. Mitina: Applied Combinatorics with Graph Theory. NEIU, 2019.

(EN)

eLearning

eLearning: currently opened course

Classification of course in study plans

  • Programme IT-MGR-2 Master's

    branch MGMe , any year of study, winter semester, elective

  • Programme IT-MGR-1H Master's

    specialization MGH , any year of study, winter semester, recommended

  • Programme MIT-EN Master's, any year of study, winter semester, compulsory-optional

Type of course unit

 

Lecture

39 hours, optionally

Teacher / Lecturer

Ing. Zbyněk Křivka, Ph.D.

Syllabus

  1. Introduction, algorithmic complexity, basic notions and graph representations.
  2. Graph searching, depth-first search, breadth-first search.
  3. Topological sort, acyclic graphs.
  4. Graph components, strongly connected components, examples.
  5. Trees, minimal spanning trees, algorithms of Jarník and Borůvka.
  6. Growing a minimal spanning tree, algorithms of Kruskal and Prim.
  7. Single-source shortest paths, Bellman-Ford algorithm, shortest path in DAGs.
  8. Dijkstra algorithm. All-pairs shortest paths.
  9. Shortest paths and matrix multiplication, Floyd-Warshall algorithm.
  10. Flows and cuts in networks, maximal flow, minimal cut, Ford-Fulkerson algorithm.
  11. Matching in bipartite graphs, maximal matching.
  12. Graph coloring.
  13. Eulerian graphs and tours, Hamiltonian graphs and cycles.

Project

13 hours, compulsory

Teacher / Lecturer

Ing. Zbyněk Křivka, Ph.D.

Syllabus

  1. Solving of selected graph problems and presentation of solutions (principle, complexity, implementation, optimization).

eLearning

eLearning: currently opened course