Fall 2015 COMP 2300 Discrete Structures for Computation Donghyun (David) Kim Department of Mathematics and Physics North Carolina Central University 1.

Slides:



Advertisements
Similar presentations
CSE 211 Discrete Mathematics
Advertisements

Chapter 8 Topics in Graph Theory
Lecture 5 Graph Theory. Graphs Graphs are the most useful model with computer science such as logical design, formal languages, communication network,
1 Slides based on those of Kenneth H. Rosen Slides by Sylvia Sorkin, Community College of Baltimore County - Essex Campus Graphs.
Discrete Mathematics and Its Applications
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.
Discrete Structures Chapter 7A Graphs Nurul Amelina Nasharuddin Multimedia Department.
CTIS 154 Discrete Mathematics II1 8.2 Paths and Cycles Kadir A. Peker.
Applied Discrete Mathematics Week 12: Trees
KNURE, Software department, Ph , N.V. Bilous Faculty of computer sciences Software department, KNURE Discrete.
Graphs Rosen 8.1, 8.2. There Are Many Uses for Graphs! Networks Data organizations Scene graphs Geometric simplification Program structure and processes.
Fall 2014 COMP 2300 Discrete Structures for Computation Donghyun (David) Kim Department of Mathematics and Physics North Carolina Central University 1.
9.2 Graph Terminology and Special Types Graphs
GRAPH Learning Outcomes Students should be able to:
Fall 2015 COMP 2300 Discrete Structures for Computation
Graphs Chapter 10.
© by Kenneth H. Rosen, Discrete Mathematics & its Applications, Sixth Edition, Mc Graw-Hill, 2007 Chapter 9 (Part 1): Graphs  Introduction to Graphs (9.1)
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.
Fall 2015 COMP 2300 Discrete Structures for Computation Donghyun (David) Kim Department of Mathematics and Physics North Carolina Central University 1.
Copyright © Cengage Learning. All rights reserved. CHAPTER 10 GRAPHS AND TREES.
1 Topics Intro. to Graphs (11.1) A B C D EF G. 2 Definition (p.650) A graph G = V(G) + E(G) A set of vertices (or nodes), V(G) = {v 1, v 2, …, v n } A.
© by Kenneth H. Rosen, Discrete Mathematics & its Applications, Sixth Edition, Mc Graw-Hill, 2007 Chapter 9 (Part 2): Graphs  Graph Terminology (9.2)
aka “Undirected Graphs”
9.2: Graph Terminology. Special Simple Graphs Complete GraphsK 1,… CyclesC 3,… WheelsW 3,… N-cubesQ 1,… Complete bipartiteK 2,2,…
Fall 2015 COMP 2300 Discrete Structures for Computation Donghyun (David) Kim Department of Mathematics and Physics North Carolina Central University 1.
Fall 2015 COMP 2300 Discrete Structures for Computation Donghyun (David) Kim Department of Mathematics and Physics North Carolina Central University 1.
1 CS104 : Discrete Structures Chapter V Graph Theory.
9.1 Introduction to Graphs
(CSC 102) Lecture 28 Discrete Structures. 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.
Fall 2015 COMP 2300 Discrete Structures for Computation Donghyun (David) Kim Department of Mathematics and Physics North Carolina Central University 1.
Fall 2015 COMP 2300 Discrete Structures for Computation Donghyun (David) Kim Department of Mathematics and Physics North Carolina Central University 1.
Fall 2015 COMP 2300 Discrete Structures for Computation Donghyun (David) Kim Department of Mathematics and Physics North Carolina Central University 1.
9 Graphs. A graph G = (V, E) consists of V, a nonempty set of vertices (or nodes) and E, a set of edges. Each edge has either one or two vertices associated.
Introduction to Graph Theory
Fall 2015 COMP 2300 Discrete Structures for Computation Donghyun (David) Kim Department of Mathematics and Physics North Carolina Central University 1.
An Introduction to Graph Theory
CSCI 115 Chapter 8 Topics in Graph Theory. CSCI 115 §8.1 Graphs.
© by Kenneth H. Rosen, Discrete Mathematics & its Applications, Sixth Edition, Mc Graw-Hill, 2007 Chapter 9 (Part 1): Graphs  Introduction to Graphs (9.1)
Graphs 9.1 Graphs and Graph Models أ. زينب آل كاظم 1.
MAT 2720 Discrete Mathematics Section 8.2 Paths and Cycles
Basic properties Continuation
Graphs Basic properties.
1 Graphs Terminology By: Sandeep Tuli Astt. Prof. CSE.
Spring 2016 COMP 2300 Discrete Structures for Computation
Spring 2016 COMP 2300 Discrete Structures for Computation Donghyun (David) Kim Department of Mathematics and Physics North Carolina Central University.
Chapter 9: Graphs.
Spring 2016 COMP 2300 Discrete Structures for Computation Donghyun (David) Kim Department of Mathematics and Physics North Carolina Central University.
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.
1 Graphs Chapters 10.1 and 10.2 University of Maryland Chapters 10.1 and 10.2 Based on slides by Y. Peng University of Maryland.
Chapter Chapter Summary Graphs and Graph Models Graph Terminology and Special Types of Graphs Representing Graphs and Graph Isomorphism Connectivity.
Chapter 9 (Part 1): Graphs
Applied Discrete Mathematics Week 13: Graphs
Graphs: Definitions and Basic Properties
Chapter 9 (Part 2): Graphs
Applied Discrete Mathematics Week 13: Graphs
Graph Graphs and graph theory can be used to model:
Chapters 8.1 and 8.2 Based on slides by Y. Peng University of Maryland
Taibah University College of Computer Science & Engineering Course Title: Discrete Mathematics Code: CS 103 Chapter 10 Graphs Slides are adopted from “Discrete.
Graphs Chapters 10.1 and 10.2 Based on slides by Y. Peng University of Maryland.
Chapters 8.1 and 8.2 Based on slides by Y. Peng University of Maryland
CS100: Discrete structures
Graph Theory What is a graph?.
Let us switch to a new topic:
Graphs: An Introduction
Presentation transcript:

Fall 2015 COMP 2300 Discrete Structures for Computation Donghyun (David) Kim Department of Mathematics and Physics North Carolina Central University 1 Chapter 10.1 Graphs: Definitions and Basic Properties

Terminologies A graph G consists of two finites sets A nonempty set V(G) of vertices. A set E(G) of edges, where each edge is associated with a set consisting of either one or two vertices called its endpoints. 2 Fall 2015 COMP 2300 Department of Mathematics and Physics Donghyun (David) Kim North Carolina Central University

Terminologies – cont’ An edge with just one endpoint is called a loop. Two or more distinct edges with the same set of endpoints are said to be parallel. An edge is said to connect its endpoints. Two vertices that are connected by an edge are called adjacent. A vertex that is an endpoint of a loop is said to be adjacent to itself. 3 Fall 2015 COMP 2300 Department of Mathematics and Physics Donghyun (David) Kim North Carolina Central University Parallel edges Loop

Terminologies – cont’ An edge is said to be incident on each of its endpoints, and two edges incident on the same endpoint are called adjacent. A vertex on which no edges are incident is called isolated. 4 Fall 2015 COMP 2300 Department of Mathematics and Physics Donghyun (David) Kim North Carolina Central University Parallel edges Loop

Drawing More Than One Picture for a Graph Consider the graph specified as follows: Vertex set = Edge set = 5 Fall 2015 COMP 2300 Department of Mathematics and Physics Donghyun (David) Kim North Carolina Central University

Directed graph A directed graph, or digraph, consists of two finite sets: a nonempty set V(G) of vertices and a set D(G) of directed edges, where each is associated with an ordered pair of vertices called its endpoints. If edge e is associated with the pair ( v,w ) of vertices, then e is said to be the (directed) edge from v to w. 6 Fall 2015 COMP 2300 Department of Mathematics and Physics Donghyun (David) Kim North Carolina Central University

Special Graphs A simple graph is a graph that does not have any loops or parallel edges. In a simple graph, an edge with endpoints v and w is denoted { v, w }. Let n be a positive integer. A complete graph on n vertices, denoted, is a simple graph with n vertices and exactly one edge connecting each pair of distinct vertices. 7 Fall 2015 COMP 2300 Department of Mathematics and Physics Donghyun (David) Kim North Carolina Central University

Complete Bipartite Graph Let m and n be positive integers. A complete bipartite graph on vertices, denoted, is a simple graph with distinct vertices, and that satisfies the following properties: For all and for all 8 Fall 2015 COMP 2300 Department of Mathematics and Physics Donghyun (David) Kim North Carolina Central University

Complete Bipartite Graph-cont’ 1.There is an edge from each vertex to each vertex 2.There is no edge from any vertex to any other vertex 3.There is no edge from any vertex to any other vertex 9 Fall 2015 COMP 2300 Department of Mathematics and Physics Donghyun (David) Kim North Carolina Central University

Subgraphs A graph H is said to be a subgraph of a graph G if, and only if, every vertex in H is also a vertex in G, every edge in H is also an edge in G, and every edge in H has the same endpoints as it has in G. 10 Fall 2015 COMP 2300 Department of Mathematics and Physics Donghyun (David) Kim North Carolina Central University

Degree of a Graph Let G be a graph and v a vertex of G. The degree of v, denoted deg( v ), equals the number of edges that are incident on v, with an edge that is a loop counted twice. The total degree of G is the sum of the degree of all the vertices of G. 11 Fall 2015 COMP 2300 Department of Mathematics and Physics Donghyun (David) Kim North Carolina Central University deg( a ): 2, deg( b ): 1, deg(c): 1, deg(d): 0 Total degree of G : 4

The Handshake Theorem If G is any graph, then the sum of the degrees of all the vertices of G equals twice the number of edges of G. Specifically, if the vertices of G are, where n is a nonnegative integer, then Total degree of G = deg( v 1 ) + deg( v 2 ) + … + deg( v n ) = 2 | E(G) | Brief Proof Each edge has to endpoints, and therefore, for the calculation of the total degree, each endpoint contributes two. If a vertex is not adjacent to any edge, its degree is 0. Otherwise, it should be adjacent to some edges. Corollary The total degree of a graph is even. A graph with four vertices of degrees 1, 1, 2, and 3 cannot exist. Proposition In any graph, there are an even number of vertices of odd degree. 12 Fall 2015 COMP 2300 Department of Mathematics and Physics Donghyun (David) Kim North Carolina Central University