Budapest University of Technology and Economics, Faculty of Electrical Engineering and Informatics

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    Graph Theory

    A tantárgy neve magyarul / Name of the subject in Hungarian: Gráfelmélet

    Last updated: 2010. november 11.

    Budapest University of Technology and Economics
    Faculty of Electrical Engineering and Informatics

    Mérnök informatikus szak

    BSc képzés

    Course ID Semester Assessment Credit Tantárgyfélév
    VISZA086   3/1/0/v 4  
    3. Course coordinator and department Dr. Fleiner Tamás,
    Web page of the course www.cs.bme.hu/....
    4. Instructors
    Name

     

    Position

     

    Department

     

    Gábor SIMONYI

     

    Professor

     

    Department of Computer Science and Information Theory

     

    Tamás FLEINER

     

    Assoc. professor

     

    Department of Computer Science and Information Theory

     

    Dávid SZESZLÉR

     

    Assoc. professor

     

    Department of Computer Science and Information Theory

     

    Gábor WIENER

     

    Assoc. professor

     

    Department of Computer Science and Information Theory

     

    Ildikó SCHLOTTER

     

    Assistant lecturer

     

    Department of Computer Science and Information Theory

     

    7. Objectives, learning outcomes and obtained knowledge

    The objective of the first part of this course is to introduce the students with some of the most important notions of graph theory and develop their skill to solve basic exercises. It is also an objective of the course that on the way they become able to identify graph theory problems in a natural way even if those appear in a different setting.

     

     

    The objective of the second part is to deepen the students' knowledge of graph theory by showing interrelations of some of the seemingly loosely related concepts and further develop their problem solving skills. Although there is no formal prerequisite for this course, some basic mathematical maturity is expected. 

     

    8. Synopsis
    1. Introduction

       

        Basic notions of graphs

     

        Why are they interesting and what are we interested in about them

     

        Trees and their main properties

     

        Coding and counting trees on n labelled vertices

     

    2. The Königsberg bridges problem and Euler tours

     

              Euler tours in directed graphs

     

              The existence of deBruijn sequences

     

              Hamiltonian cycles

     

              The different nature of Hamiltonian cycles and Euler tours

     

              Necessary conditions for Hamiltonicity

     

              Sufficient conditions for Hamiltonicity due to Dirac, Pósa, Ore, and Chvátal

     

    1. Matchings and their relevance

       

              Necessary and sufficient conditions for the existence of a perfect matching in   bipartite graphs

     

              Kőnig's min-max theorem

     

              Perfect matchings in general graphs, Tutte's criterion

     

              Stable matchings and their use

     

        The existence of stable matchings in bipartite graphs

     

    1. Network flows

       

              The augmenting paths algorithm

     

              The Ford-Fulkerson min-max result and its relation to Kőnig's one

     

              Menger's min-max results

     

              The relevance of min-max formulae in general

     

    1. Planarity,

       

              Euler's formula and Kuratowski's criterion

     

              Minors and Wagner's criterion

     

              The equivalence of forbidding the Kuratowski graphs as minors and as topological    

     

              subgraphs

     

    1. Coloring graphs as a model for scheduling

       

               Bounding the chromatic number from above, greedy algorithm

     

               Bounding the chromatic number from below, Mycielski's construction

     

               Coloring edges

     

         Line graphs and the analogs of the previous bounds

     

         Improving the greedy algorithm, Vizing's upper bound

     

    1. Coloring planar graphs, 4-color theorem and 5-color theorem,

       

        Tait's result on the the relation of edge-coloring cubic planar graphs and the 4-color     

     

        theorem

     

        Perfect graphs, perfectness of bipartite graphs, their line graphs and the complements

     

        of these

     

        Odd holes, odd antiholes and their relevance

     

        Relation of complementation and perfectness in general

     

    8. List coloring

     

        Relation of the list coloring number to the chromatic number, list coloring conjecture

     

        Galvin's theorem and its relation to stable matchings

     

              List coloring planar graphs

     

        Thomassen's inductive argument

     

        Voigt's construction for the sharpness of Thomassen's result

     

    1. Extremal graph theory

       

              Turán's sharp upper bound on the number of edges if the clique number is bounded

     

        The Erdős-Stone theorem and the Erdős-Simonovits limit result

     

              The Kővari-T.Sós-Turán upper bound for the analogous bipartite problem

     

    1. Ramsey theory

       

        Basic Ramsey-type results in graph theory

     

        Examples of Ramsey-type results outside graph theory

     

        Ramsey numbers, upper and lower bounds

     

    1. Hypergraphs as generalizations of graphs and as set systems

       

              Ramsey's result in the hypergraph setting

     

              Sperner systems and their maximum possible size

     

              LYM inequality

     

              Intersecting set systems, Erdős-Ko-Rado theorem

     

    1. Kneser's conjecture as a problem on hypergraphs

       

              Kneser graphs and their chromatic number, the Lovász-Kneser theorem

     

              Kneser graphs and fractional colorings

     

    9. Method of instruction Lectures and recitations

     

    10. Assessment The grade given will be based on four homework assignments consisting of five problems each, and on the final exam. The solutions should be handed in by the due date that will be on the 4th, 6th, 9th and 11th weeks, respectively. The assignments will be handed out at least a week before the due date. (Please note that no late homework will be accepted.) The assignments weigh 15% each while the final exam weighs 40% in calculating the final score.

     

    12. Consultations You can reach the instructor at the following e-mail address for consultation:

     

    Gábor SIMONYI: simonyi@renyi.hu

     

    13. References, textbooks and resources

    Reinhard Diestel: Graph Theory, 3rd Edition, Springer-Verlag, Heidelberg, 2005;  or  

     

    Béla Bollobás: Modern Graph Theory, Springer-Verlag, Heidelberg, Corr. 2nd printing 2002.

     

    Additional useful reading: Martin Aigner, Günter Ziegler:Proofs from the Book, Springer-Verlag, Heidelberg, 1998.

     

    14. Required learning hours and assignment
    Number of contact hours

     

    56

     

    Preparation to the classes

     

    14

     

    Preparation to the tests

     

     

    Homework

     

    30

     

    Assigned reading

     

     

    Preparation to the exam

     

    20

     

    Total

     

    120

     

    15. Syllabus prepared by
    Name

     

    Position

     

    Department

     

    Gábor SIMONYI

     

    Professor

     

    Department of Computer Science and Information Theory