MATH 310, FALL 2003 (Combinatorial Problem Solving) Lecture 3, Friday, September 5.

Slides:



Advertisements
Similar presentations
 Theorem 5.9: Let G be a simple graph with n vertices, where n>2. G has a Hamilton circuit if for any two vertices u and v of G that are not adjacent,
Advertisements

22C:19 Discrete Math Graphs Fall 2010 Sukumar Ghosh.
Graph-02.
Introduction to Graphs
1 Section 8.2 Graph Terminology. 2 Terms related to undirected graphs Adjacent: 2 vertices u & v in an undirected graph G are adjacent (neighbors) in.
SE561 Math Foundations Week 11 Graphs I
MATH 310, FALL 2003 (Combinatorial Problem Solving) Lecture 19, Friday, October 17.
02/01/05Tucker, Sec Applied Combinatorics, 4th Ed. Alan Tucker Section 1.3 Edge Counting Prepared by Joshua Schoenly and Kathleen McNamara.
Graph Theory in CS Route Search in Online Map Services
MATH 310, FALL 2003 (Combinatorial Problem Solving) Lecture 15, Friday, October 3.
Chapter 1 Review Homework (MATH 310#3M):
Discrete Structures Chapter 7A Graphs Nurul Amelina Nasharuddin Multimedia Department.
CTIS 154 Discrete Mathematics II1 8.2 Paths and Cycles Kadir A. Peker.
MATH 310, FALL 2003 (Combinatorial Problem Solving) Lecture 11, Wednesday, September 24.
MATH 310, FALL 2003 (Combinatorial Problem Solving) Lecture 5,Wednesday, September 10.
Applied Discrete Mathematics Week 12: Trees
Graphs.
MATH 310, FALL 2003 (Combinatorial Problem Solving) Lecture 6, Friday, September 12.
MATH 310, FALL 2003 (Combinatorial Problem Solving) Lecture 4, Monday, September 8.
MATH 310, FALL 2003 (Combinatorial Problem Solving) Lecture 10, Monday, September 22.
MTH118 Sanchita Mal-Sarkar. Routing Problems The fundamental questions: Is there any proper route for the particular problem? If there are many possible.
Section 1.2 Isomorphisms By Christina Touhey and Sarah Graham.
Discrete Mathematics Lecture 9 Alexander Bukharovich New York University.
1/22/03Tucker, Applied Combinatorics, Section EDGE COUNTING TUCKER, APPLIED COMBINATORICS, SECTION 1.3, GROUP B Michael Duquette & Amanda Dargie.
9.2 Graph Terminology and Special Types Graphs
GRAPH Learning Outcomes Students should be able to:
Graph Theoretic Concepts. What is a graph? A set of vertices (or nodes) linked by edges Mathematically, we often write G = (V,E)  V: set of vertices,
1 Graphs Chapters 9.1 and 9.2 University of Maryland Chapters 9.1 and 9.2 Based on slides by Y. Peng University of Maryland.
5.1  Routing Problems: planning and design of delivery routes.  Euler Circuit Problems: Type of routing problem also known as transversability problem.
Lecture 5.2: Special Graphs and Matrix Representation CS 250, Discrete Structures, Fall 2013 Nitesh Saxena Adopted from previous lectures by Zeph Grunschlag.
Fall 2015 COMP 2300 Discrete Structures for Computation Donghyun (David) Kim Department of Mathematics and Physics North Carolina Central University 1.
Lecture 10: Graphs Graph Terminology Special Types of Graphs
aka “Undirected Graphs”
Copyright © Zeph Grunschlag, More on Graphs.
9.1 Introduction to Graphs
Graphs.  Definition A simple graph G= (V, E) consists of vertices, V, a nonempty set of vertices, and E, a set of unordered pairs of distinct elements.
Week 11 - Monday.  What did we talk about last time?  Binomial theorem and Pascal's triangle  Conditional probability  Bayes’ theorem.
5.4 Graph Models (part I – simple graphs). Graph is the tool for describing real-life situation. The process of using mathematical concept to solve real-life.
Data Structures & Algorithms Graphs
September1999 CMSC 203 / 0201 Fall 2002 Week #13 – 18/20/22 November 2002 Prof. Marie desJardins.
5.5.2 M inimum spanning trees  Definition 24: A minimum spanning tree in a connected weighted graph is a spanning tree that has the smallest possible.
Chapter 5 Graphs  the puzzle of the seven bridge in the Königsberg,  on the Pregel.
Graph.
Graph Theory and Applications
Graph Theory. A branch of math in which graphs are used to solve a problem. It is unlike a Cartesian graph that we used throughout our younger years of.
Lecture 10: Graph-Path-Circuit
Introduction to Graphs. This Lecture In this part we will study some basic graph theory. Graph is a useful concept to model many problems in computer.
Graphs 9.1 Graphs and Graph Models أ. زينب آل كاظم 1.
Graph theory and networks. Basic definitions  A graph consists of points called vertices (or nodes) and lines called edges (or arcs). Each edge joins.
GRAPHS. Graph Graph terminology: vertex, edge, adjacent, incident, degree, cycle, path, connected component, spanning tree Types of graphs: undirected,
MAT 2720 Discrete Mathematics Section 8.2 Paths and Cycles
Graphs Basic properties.
Graph Theory Unit: 4.
Basic Operations on Graphs Lecture 5.. Basic Operations on Graphs Deletion of edges Deletion of vertices Addition of edges Union Complement Join.
Chapter 11 - Graph CSNB 143 Discrete Mathematical Structures.
Introduction to Graph Theory
Chap 7 Graph Def 1: Simple graph G=(V,E) V : nonempty set of vertices E : set of unordered pairs of distinct elements of V called edges Def 2: Multigraph.
1 GRAPH Learning Outcomes Students should be able to: Explain basic terminology of a graph Identify Euler and Hamiltonian cycle Represent graphs using.
رياضيات متقطعة لعلوم الحاسب MATH 226. Chapter 10.
CSNB 143 Discrete Mathematical Structures
Matrix Representation of Graphs
Lecture 5.2: Special Graphs and Matrix Representation
Lecture 19: CONNECTIVITY Sections
Applied Discrete Mathematics Week 13: Graphs
15. Directed graphs and networks
2.3 Graph Coloring Homework (MATH 310#3W):
Can you draw this picture without lifting up your pen/pencil?
Relations (sections 7.1 – 7.5)
Lecture 5.3: Graph Isomorphism and Paths
Applied Discrete Mathematics Week 13: Graphs
Presentation transcript:

MATH 310, FALL 2003 (Combinatorial Problem Solving) Lecture 3, Friday, September 5

Complete graph K n. A graph on n vertices in which each vertex is adjacent to all other vertices is called a complete graph on n vertices, denoted by K n. K 20

Some complete graphs Here are some complete graphs. For each one determine the number of vertices, edges, and the degree of each vertex. Every graph on n vertices is a subgraph of K n.

Example 2: Isomorphism in Symmetric Graphs The two graphs on the left are isomorphic. Top graph vertices clockwise: a,b,c,d,e,f,g Bottom graph vertices clockwise: 1,2,3,4,5,6,7 Possible isomorphism:a-1,b- 5,c-2,d-6,e-3,f-7,g-4.

Example 3: Isomorphism of Directed Graphs Some hints how to prove non-isomorphism: If two graphs are not isomorphic as undirected graphs, they cannot be isomorphic as directed graphs. (p,q) –label on a vertex: indegree p, outdegree q. Look at the directed edges and their (p,q,r,s) labels! 1 23 (p,q,r,s) (r,s) (2,3) (p,q) e

1.3. Edge Counting Homework (MATH 310#1F): Read 1.4. Write down a list of all newly introduced terms (printed in boldface) Do Exercises1.3: 4,6,8,12,13 Volunteers: ____________ Problem: 13. News: News: Please always bring your updated list of terms to class meeting. Please always bring your updated list of terms to class meeting. Homework in now labeled for easier identification: Homework in now labeled for easier identification: (MATH 310, #, Day-MWF)(MATH 310, #, Day-MWF)

Theorem 1 In any graph, the sum of the degrees of all vertices is equal to twice the number of edges.

Corollary In any graph, the number of vertices of odd degree is even.

Example 2: Edges in a Complete Graph The degree of each vertex of K n is n-1. There are n vertices. The total sum is n(n- 1) = twice the number of edges. K n has n(n-1)/2 edges. On the left K 15 has 105 edges.

Example 3: Impossible graph Is it possible to have a group of seven people such that each person knows exactly three other people in the group?

Bipartite Graphs A graph G is bipartite if its vertices can be partitioned into two sets V L and V R and every edge joins a vertex in V L with a vertex in V R Graph on the left is biparite.

Theorem 2 A graph G is bipartite if and only if every circuit in G has even length.

Example 5: Testing for a Bipartite Graph Is the graph on the left bipartite?