Definition 8: Graphs that have a number assigned to each edge or each vertex are called weighted graphs weighted digraphs.

Slides:



Advertisements
Similar presentations
Chapter 8 Topics in Graph Theory
Advertisements

Lecture 5 Graph Theory. Graphs Graphs are the most useful model with computer science such as logical design, formal languages, communication network,
Graph-02.
 期中测验时间:本周五上午 9 : 40  教师 TA 答疑时间 : 周三晚上 6 : 00—8 : 30  地点:软件楼 315 房间,  教师 TA :李弋老师  开卷考试.
Review Binary Search Trees Operations on Binary Search Tree
1 Slides based on those of Kenneth H. Rosen Slides by Sylvia Sorkin, Community College of Baltimore County - Essex Campus Graphs.
1 Representing Graphs. 2 Adjacency Matrix Suppose we have a graph G with n nodes. The adjacency matrix is the n x n matrix A=[a ij ] with: a ij = 1 if.
Applied Discrete Mathematics Week 12: Trees
1 Section 8.4 Connectivity. 2 Paths In an undirected graph, a path of length n from u to v, where n is a positive integer, is a sequence of edges e 1,
Applied Discrete Mathematics Week 12: Trees
KNURE, Software department, Ph , N.V. Bilous Faculty of computer sciences Software department, KNURE Discrete.
Discrete Mathematics Lecture 9 Alexander Bukharovich New York University.
9.2 Graph Terminology and Special Types Graphs
GRAPH Learning Outcomes Students should be able to:
5.4 Shortest-path problem  Let G=(V,E,w) be a weighted connected simple graph, w is a function from edges set E to position real numbers set. We denoted.
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,
7.1 and 7.2: Spanning Trees. A network is a graph that is connected –The network must be a sub-graph of the original graph (its edges must come from the.
© by Kenneth H. Rosen, Discrete Mathematics & its Applications, Sixth Edition, Mc Graw-Hill, 2007 Chapter 9 (Part 2): Graphs  Graph Terminology (9.2)
1 CS104 : Discrete Structures Chapter V Graph Theory.
Based on slides by Y. Peng University of Maryland
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.
Chapter 1 Fundamental Concepts Introduction to Graph Theory Douglas B. West July 11, 2002.
Chapter 5 Graphs  the puzzle of the seven bridge in the Königsberg,  on the Pregel.
1 Graphs Theory UNIT IV. 2Contents  Basic terminology,  Multi graphs and weighted graphs  Paths and circuits  Shortest path in weighted graph  Hamiltonian.
 Quotient graph  Definition 13: Suppose G(V,E) is a graph and R is a equivalence relation on the set V. We construct the quotient graph G R in the follow.
Basic properties Continuation
Discrete Structures CISC 2315 FALL 2010 Graphs & Trees.
Chapter 9: Graphs.
Week 11 - Wednesday.  What did we talk about last time?  Graphs  Paths and circuits.
1. 期中测验时间和地点: 11 月 4 日, 上午 9:40—11 : 40 地点: 教室 2. 答疑时间和地点: 1)11 月 1 日 ( 周五 )13:00—15:00 软件楼 319 2)11 月 2 日和 3 日, 14:00—17:00 软件楼 3 楼 机房讨论室.
1 GRAPH Learning Outcomes Students should be able to: Explain basic terminology of a graph Identify Euler and Hamiltonian cycle Represent graphs using.
1 Lecture 5 (part 2) Graphs II (a) Circuits; (b) Representation Reading: Epp Chp 11.2, 11.3
رياضيات متقطعة لعلوم الحاسب MATH 226. Chapter 10.
Trees.
An Introduction to Graph Theory
Applied Discrete Mathematics Week 14: Trees
Chapter 9 (Part 2): Graphs
Let us switch to a new topic:
Applied Discrete Mathematics Week 13: Graphs
Special Graphs By: Sandeep Tuli Astt. Prof. CSE.
Graphs Hubert Chan (Chapter 9) [O1 Abstract Concepts]
Representing Graphs and
Chapter 5 Fundamental Concept
Graph theory Definitions Trees, cycles, directed graphs.
Agenda Lecture Content: Introduction to Graph Path and Cycle
Discrete Structures – CNS2300
Taibah University College of Computer Science & Engineering Course Title: Discrete Mathematics Code: CS 103 Chapter 10 Graphs Slides are adopted from “Discrete.
Advanced Algorithms Analysis and Design
Graphs.
Based on slides by Y. Peng University of Maryland
Can you draw this picture without lifting up your pen/pencil?
Relations (sections 7.1 – 7.5)
CS100: Discrete structures
G-v, or G-{v} When we remove a vertex v from a graph, we must remove all edges incident with the vertex v. When a edge is removed from a graph, without.
Connectivity Section 10.4.
Walks, Paths, and Circuits
Representing Graphs Wade Trappe.
Theorem 5.13: For vT‘, l’(v)= min{l(v), l(vk)+w(vk, v)}
10.4 Connectivity Dr. Halimah Alshehri.
Graphs G = (V, E) V are the vertices; E are the edges.
N(S) ={vV|uS,{u,v}E(G)}
5/9/2019 Discrete Math II Howon Kim
Discrete Mathematics for Computer Science
Paths and Connectivity
9.4 Connectivity.
Paths and Connectivity
Applied Discrete Mathematics Week 13: Graphs
Based on slides by Y. Peng University of Maryland
Agenda Review Lecture Content: Shortest Path Algorithm
Presentation transcript:

Definition 8: Graphs that have a number assigned to each edge or each vertex are called weighted graphs weighted digraphs

Definition 9: The graph G'(V',E') is called a subgraph of G(V,E) If V'V and E'E. If V'=V, then G'(V,E') is said to be a spanning subgraph.

Definition 10: If G'(V',E') contains all edges of G that join two vertices in V' then G' is called the induced subgraph by V'V and is denoted by G(V'). induced subgraph by {v1,v2,v4,v5}

G-v, or G-{v} When we remove a vertex v from a graph, we must remove all edges incident with the vertex v. When a edge is removed from a graph, without removing endpoints of the edge

Adjacency matrices and Incidence matrices Definition 12: Let G(V,E) be a graph of non-multiple edge where |V|=n. Suppose that v1,v2,…,vn are the vertices. The adjacency matrix A of G, with respect to this listing of the vertices, is the nn zero-one matrix with 1 as its (i,j)th entry when vi and vj are adjacent, and 0 as its (i,j)th entry when they are not adjacent. In other words, If its adjacency matrix is A=[aij], then

Let G(V,E) be an undirected graph Let G(V,E) be an undirected graph. Suppose that v1,v2,…,vn are the vertices and e1,e2,…,em are the edges of G. Then the incidence matrix with respect to this ordering of V and E is the nm matrix M=[mij], where

Quotient graph Definition 13: Suppose G(V,E) is a graph and R is a equivalence relation on the set V. We construct the quotient graph GR in the follow way. The vertices of GR are the equivalence classes of V produced by R. If [v] and [w] are the equivalence classes of vertices v and w of G, then there is an edge in GR between [v] and [w] if some vertex in [v] is connected to some vertex in [w] in the graph G.

5.2 Paths and Circuits 5.2.1 Paths and Circuits Definition 14: Let n be a nonnegative integer and G be an undirected graph. A path of length n from u to v in G is a sequence of edges e1,e2,…,en of G such that e1={v0=u,v1}, e2={v1,v2},…,en={vn-1,vn=v}, and no edge occurs more than once in the edge sequence. When G is a simple graph, we denote this path by its vertex sequence u=v0,v1,…,vn=v. A path is called simple if no vertex appear more than once. A circuit is a path that begins and ends with the same vertex. A circuit is simple if the vertices v1,v2,…,vn-1 are all distinct

(e6,e7,e1) is a path of from v2 to v1 (e6,e7,e8,e4,e7) is not a circuit; (e1,e6,e7,e8,e4,e5) is a circuit (e1,e8,e4,e5) is a simple circuit (e6,e7) is a simple circuit (e6,e7,e8,e4,e7,e1) is not a path; (e6,e7,e1) is a path of from v2 to v1 (e8,e4,e5) is a simple path of from v2 to v1

Theorem 5.4:Let  (G)≥2, then there is a simple circuit in the graph G. Proof: If graph G contains loops or multiple edges, then there is a simple circuit. (a,a) or (e,e'). Let G be a simple graph. For any vertex v0 of G, d(v0)≥2, next vertex, adjacent, Pigeonhole principle

5.2.2 Connectivity Definition 15: A graph is called connectivity if there is a path between every pair of distinct vertices of the graph. Otherwise , the graph is disconnected.

components of the graph G1,G2,…,Gω

A graph that is not connected is the union of two or more connected subgraphs, each pair of which has no vertex in common. These disjoint connected subgraphs are called the connected components of the graph

Example: Let G be a simple graph Example: Let G be a simple graph. If G has n vertices, e edges, and ω connected components , then Proof: e≥n-ω Let us apply induction on the number of edges of G. e=0, isolated vertex,has n components ,n=ω, 0=e≥n-ω=0,the result holds Suppose that result holds for e=e0-1 e=e0, Omitting any edge , G', (1)G' has n vertices, ω components and e0-1 edges. (2)G' has n vertices, ω+1 components and e0-1 edges

2. Let G1,G2,…,Gωbe ω components of G. Gi has ni vertices for i=1,2,…, ω, and n1+n2+…+nω=n,and n1≥n2≥…≥nω, and

If G is connected, then the number of edges of G has at least n-1 edges. Tree.

5.2.3 Connectivity in directed graphs Definition 16: Let n be a nonnegative integer and G be a directed graph. A path of length n from u to v in G is a sequence of edges e1,e2,…,en of G such that e1=(v0=u,v1), e2=(v1,v2), …, en=(vn-1,vn=v), and no edge occurs more than once in the edge sequence. A path is called simple if no vertex appear more than once. A circuit is a path that begins and ends with the same vertex. A circuit is simple if the vertices v0,v1,…,vn are all distinct.

(e1,e2,e7,e1,e2,e7)is not a circuit (e1,e2,e7,e6,e12) is a circuit (e1,e2,e7) is a simple circuit. (a,b,c,a) (e1,e2,e7,e1,e2,e9)is not a path (e1,e2,e7,e6,e9)is a path from a to e (e1,e2,e9)is a path from a to e, is a simple path. (a,b,c,e)

Definition 17: A directed graph is strongly connected if there is a path from a to b and from b to a whenever a and b are vertices in the graph. A directed graph is connected directed graph if there is a path from a to b or b to a whenever a and b are vertices in the graph. A directed graph is weakly connected if there is a path between every pair vertices in the underlying undirected graph.

(a)strongly connected (b)connected directed (c)weakly connected strongly connected components: G1,G2,…,Gω

V ={v1,v2,v3,v4,v5,v6,v7, v8} V1={v1,v7,v8}, V2={v2,v3,v5,v6}, V3={v4}, strongly connected components : G(V1),G(V2),G(V3)

Next: Bipartite graph, Euler paths and circuits, P296 8.2

Exercise P128 11;P295 11, 17,19,22,23,28 1.Prove that the complement of a disconnected graph is connected. 2.Let G be a simple graph with n vertices. Show that ifδ(G) >[n/2]-1, then G is connected. 3.Show that a simple graph G with n vertices are connected if it has more than (n-1)(n-2)/2 edges. 4.Represent each of these graphs with an adjacency matrix an incidence matrix.