Course details

Graph Algorithms

GAL Acad. year 2024/2025 Winter semester 5 credits

Current academic year

This course discusses graph representations and graphs algorithms for searching (depth-first search, breadth-first search), topological sorting, 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.

Guarantor

Meduna Alexandr, prof. RNDr., CSc. (DIFS)

Course coordinator

Křivka Zbyněk, Ing., Ph.D. (DIFS)

Language of instruction

Czech, English

Completion

Examination (written)

Time span

  • 39 hrs lectures
  • 13 hrs projects

Assessment points

  • 60 pts final exam (written part)
  • 15 pts mid-term test (written part)
  • 25 pts projects

Department

Department of Information Systems (UIFS)

Lecturer

Křivka Zbyněk, Ing., Ph.D. (DIFS)

Instructor

Kožár Tomáš, Ing.
Křivka Zbyněk, Ing., Ph.D. (DIFS)

Learning objectives

Familiarity with graphs and graph algorithms with their complexities.
Fundamental ability to construct an algorithm for a graph problem and to analyze its time and space complexity.

Prerequisite knowledge and skills

Foundations in discrete mathematics and algorithmic thinking.

Study literature

  • T.H. Cormen, C.E. Leiserson, R.L. Rivest, C. Stein, Introduction to Algorithms, 3rd edition. MIT Press, 2009.
  • J.A. McHugh, Algorithmic Graph Theory, Prentice-Hall, 1990.
  • K. Erciyes: Guide to Graph Algorithms (Sequential, Parallel and Discributed). Springer, 2018.

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

Syllabus of lectures

  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, the Bellman-Ford algorithm, shortest path in DAGs.
  8. Dijkstra's algorithm. All-pairs shortest paths.
  9. Shortest paths and matrix multiplication, the Floyd-Warshall algorithm.
  10. Flows and cuts in networks, maximal flow, minimal cut, the Ford-Fulkerson algorithm.
  11. Matching in bipartite graphs, maximal matching.
  12. Graph coloring, Chromatic polynomial.
  13. Eulerian graphs and tours, Chinese postman problem, and Hamiltonian cycles.

Syllabus - others, projects and individual work of students

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

Progress assessment

  • Mid-term written examination (15 point)
  • Evaluated project(s) (25 points)
  • Final written examination (60 points)
  • The minimal number of points which can be obtained from the final exam is 25. Otherwise, no points will be assigned to a student.


In case of illness or another serious obstacle, the student should inform the faculty about that and subsequently provide the evidence of such an obstacle. Then, it can be taken into account within evaluation:

  • The student can ask the responsible teacher to extend the time for the project assignment.
  • If a student cannot attend the mid-term exam, (s)he can ask to derive points from the evaluation of his/her first attempt of the final exam.

Schedule

DayTypeWeeksRoomStartEndCapacityLect.grpGroupsInfo
Fri lecture lectures L314 12:0014:5030 1MIT 2MIT NMAT NNET xx Křivka

Course inclusion in study plans

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