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Algorithmic Graph Theory (ΠΛ4): Διαφορά μεταξύ των αναθεωρήσεων

Algorithmic Graph Theory (ΠΛ4): Διαφορά μεταξύ των αναθεωρήσεων

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[[Graduate Courses Outlines]] - [https://math.uoi.gr  Department of Mathematics]
=== General ===
=== General ===


Αναθεώρηση της 08:51, 2 Ιουλίου 2022

Graduate Courses Outlines - Department of Mathematics

General

School School of Science
Academic Unit Department of Mathematics
Level of Studies Graduate
Course Code ΠΛ4Α
Semester 2
Course Title Algorithmic Graph Theory
Independent Teaching Activities Lectures (Weekly Teaching Hours: 3, Credits: 7.5)
Course Type Special Background
Prerequisite Courses -
Language of Instruction and Examinations Greek
Is the Course Offered to Erasmus Students Yes (in English)
Course Website (URL) -

Learning Outcomes

Learning outcomes This course aims at introducing to students fundamental algorithmic techniques for solving problems related and modeled by graphs. After successfully passing this course the students will be able to:
  1. Understand graph theory.
  2. Design and analyze algorithms for graph problems.
  3. Understand difficult problems on graph classes.
General Competences
  1. Search for, analysis and synthesis of data and information, with the use of the necessary technology
  2. Working independently
  3. Team work
  4. Project planning and management

All the above will give to the stundetns the opportunity to work in an international multidisciplinary environment.

Syllabus

  1. Fundamental Graph Theory
  2. Algorithmic and Combinatorial Graph Problems
  3. Complexity Classes and Parameterized Algorithms
  4. Chordal graphs, Comparability graphs, Split graphs
  5. Permutation graphs, Interval graphs, Cographs, Threshold graphs
  6. Algorithmic problems and width parameters

Teaching and Learning Methods - Evaluation

Delivery In the class
Use of Information and Communications Technology Use of projector and interactive board during lectures.
Teaching Methods
Activity Semester Workload
Lectures 39
Study and analysis of bibliography 78
Preparation of assignments and interactive teaching 70.5
Course total 187.5
Student Performance Evaluation
  1. Written work (50%)
  2. Essay / report (20%)
  3. Public presentation (30%)

Attached Bibliography

  1. [Go2004] M. Golumbic, Algorithmic Graph Theory and Perfect Graphs, NORTH-HOLLAND, 2004.
  2. [BSL99] A. Brandstädt, J. Spinrad, and V. Lee, Graph Classes: A Survey, SIAM Monographs on Discrete Math. and Applications, 1999.
  3. [NPG15] Nikolopoulos, S., Georgiadis, L., Palios, L., Algorithmic Graph Theory. Kallipos, 2015.
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