Compatible circuits in eulerian digraphs

Size: px
Start display at page:

Download "Compatible circuits in eulerian digraphs"

Transcription

1 Compatible circuits in eulerian digraphs James Carraher University of Nebraska Lincoln Joint Work with Stephen Hartke March 2012 James Carraher (UNL) Compatible circuits in eulerian digraphs 1 / 17

2 Introduction Definition: An eulerian digraph G is a digraph graph that contains a closed walk that visits each edge exactly once. Theorem. A digraph G is eulerian if and only if deg ( ) = deg + ( ) for all vertices and G is strongly (weakly) connected James Carraher (UNL) Compatible circuits in eulerian digraphs 2 / 17

3 Introduction Definition: An eulerian digraph G is a digraph graph that contains a closed walk that visits each edge exactly once. Theorem. A digraph G is eulerian if and only if deg ( ) = deg + ( ) for all vertices and G is strongly (weakly) connected James Carraher (UNL) Compatible circuits in eulerian digraphs 2 / 17

4 Introduction Eulerian digraphs can be applied to routing problems such as garbage collecting, mail carriers, etc. Eulerian undirected graphs can be applied to reconstructing DNA from its segments. James Carraher (UNL) Compatible circuits in eulerian digraphs 3 / 17

5 Compatible Circuits Definition: A colored eulerian digraph G is an eulerian digraph with a given edge coloring (not necessarily proper). Definition: A compatible circuit is an eulerian circuit of G such that no two consecutive edges in the tour have the same color (i.e. no monochromatic transitions). 1 Good Bad James Carraher (UNL) Compatible circuits in eulerian digraphs 4 / 17

6 Compatible Circuits Definition: A colored eulerian digraph G is an eulerian digraph with a given edge coloring (not necessarily proper). Definition: A compatible circuit is an eulerian circuit of G such that no two consecutive edges in the tour have the same color (i.e. no monochromatic transitions). 1 Good Bad James Carraher (UNL) Compatible circuits in eulerian digraphs 4 / 17

7 Compatible Circuits Big Question: When does an colored eulerian digraph have a compatible circuit? Not all graphs have compatible circuits. James Carraher (UNL) Compatible circuits in eulerian digraphs 5 / 17

8 Compatible Circuits Let γ( ) be the size of the largest color class incident to. v James Carraher (UNL) Compatible circuits in eulerian digraphs 6 / 17

9 Compatible Circuits Let γ( ) be the size of the largest color class incident to. If G is a colored eulerian digraph and there exists a vertex where γ( ) > deg + ( ), then G does not have a compatible circuit. Example v James Carraher (UNL) Compatible circuits in eulerian digraphs 6 / 17

10 Compatible Circuits Theorem [Kotzig, 1968] If G is a colored eulerian undirected graph and γ( ) deg( )/2 then G has a compatible circuit. James Carraher (UNL) Compatible circuits in eulerian digraphs 7 / 17

11 Compatible Circuits Theorem [Kotzig, 1968] If G is a colored eulerian undirected graph and γ( ) deg( )/2 then G has a compatible circuit. A colored eulerian digraph with γ( ) deg + ( ) does not necessarily have a compatible circuit. James Carraher (UNL) Compatible circuits in eulerian digraphs 7 / 17

12 Compatible Circuits Splitting a vertex where γ( ) = deg + ( ). G G v G' G' v 1 v 2 The graph G has a compatible circuit if and only if the graph G has a compatible circuit. James Carraher (UNL) Compatible circuits in eulerian digraphs 8 / 17

13 Compatible Circuits Splitting a vertex where γ( ) = deg + ( ). G G v G' G' v 1 v 2 The graph G has a compatible circuit if and only if the graph G has a compatible circuit. James Carraher (UNL) Compatible circuits in eulerian digraphs 8 / 17

14 Fixable vertices Let T be an eulerian circuit of G and a vertex of G. We define the excursion graph L T ( ) to be the following graph. G v L (v) T v James Carraher (UNL) Compatible circuits in eulerian digraphs 9 / 17

15 Fixable vertices Let T be an eulerian circuit of G and a vertex of G. We define the excursion graph L T ( ) to be the following graph. G v L (v) T v Definition: A vertex is fixable if L M ( ) has a compatible circuit for any matching M between E + ( ) and E ( ). James Carraher (UNL) Compatible circuits in eulerian digraphs 9 / 17

16 Fixable vertices Proposition. Let G be a colored eulerian digraph. If every vertex of G is a fixable vertex then G has a compatible circuit. Idea: Iteratively fix fixable vertices. James Carraher (UNL) Compatible circuits in eulerian digraphs 10 / 17

17 Fixable vertices Proposition. Let G be a colored eulerian digraph. If every vertex of G is a fixable vertex then G has a compatible circuit. Idea: Iteratively fix fixable vertices. Proposition. A vertex with γ( ) < deg + ( ) is fixable if and only if it does not have the form below. James Carraher (UNL) Compatible circuits in eulerian digraphs 10 / 17

18 Fixable vertices Proposition. Let G be a colored eulerian digraph. If every vertex of G is a fixable vertex then G has a compatible circuit. Idea: Iteratively fix fixable vertices. Proposition. A vertex with γ( ) < deg + ( ) is fixable if and only if it does not have the form below. Example The excursion graph L M ( ) does not have a compatible circuit. James Carraher (UNL) Compatible circuits in eulerian digraphs 10 / 17

19 Non-fixable vertices Let S be the set of vertices that are not fixable. Let S 3 be the subset of S with vertices of outdegree three. I.e. We will consider colored eulerian digraphs with no nonfixable vertices of outdegree three. James Carraher (UNL) Compatible circuits in eulerian digraphs 11 / 17

20 Non-fixable vertices Some Auxiliary Graphs The graph G, G S, and component graph H G. G G S A B C A C H G B D D James Carraher (UNL) Compatible circuits in eulerian digraphs 12 / 17

21 Non-fixable vertices Some Auxiliary Graphs The graph G, G S, and component graph H G. G G S A B C A C H G B D D James Carraher (UNL) Compatible circuits in eulerian digraphs 12 / 17

22 Non-fixable vertices Problem: Let H be a multigraph whose edge set is the disjoint union of 2-trails. When does there exist a subset E of the edges such that 1 E contains at most one edge from each 2-trail, and 2 the spanning subgraph with edge set E is connected? James Carraher (UNL) Compatible circuits in eulerian digraphs 13 / 17

23 Non-fixable vertices Problem: Let H be a multigraph whose edge set is the disjoint union of 2-trails. When does there exist a subset E of the edges such that 1 E contains at most one edge from each 2-trail, and 2 the spanning subgraph with edge set E is connected? A multigraph H with the property above will be said to contain a rainbow spanning tree. James Carraher (UNL) Compatible circuits in eulerian digraphs 13 / 17

24 Non-fixable vertices Theorem. Let G be a colored eulerian digraph with no nonfixable vertices of outdegree three. Then G has a compatible circuit if and only if the component graph H G contains a rainbow spanning tree. James Carraher (UNL) Compatible circuits in eulerian digraphs 14 / 17

25 Non-fixable vertices Theorem. Let G be a colored eulerian digraph with no nonfixable vertices of outdegree three. Then G has a compatible circuit if and only if the component graph H G contains a rainbow spanning tree. G G S A B C A C H G B D D James Carraher (UNL) Compatible circuits in eulerian digraphs 14 / 17

26 Non-fixable vertices Prop. A multigraph H has a rainbow spanning tree iff (# 2-trails in a cut S) + 1 # components in H S. Comment: There is a polynomial time algorithm to determine if a multigraph H contains a rainbow spanning tree. James Carraher (UNL) Compatible circuits in eulerian digraphs 15 / 17

27 Non-fixable vertices Graphs with nonfixable outdegree 3 vertices. James Carraher (UNL) Compatible circuits in eulerian digraphs 16 / 17

28 Non-fixable vertices Compatible circuits in eulerian digraphs James Carraher University of Nebraska Lincoln Joint Work with Stephen Hartke March 2012 James Carraher (UNL) Compatible circuits in eulerian digraphs 17 / 17

Eulerian circuits with no monochromatic transitions

Eulerian circuits with no monochromatic transitions Eulerian circuits with no monochromatic transitions James Carraher University of Nebraska Lincoln s-jcarrah1@math.unl.edu Joint Work with Stephen Hartke June 2012 James Carraher (UNL) Eulerian circuits

More information

Compatible circuits in eulerian digraphs

Compatible circuits in eulerian digraphs Compatible circuits in eulerian digraphs James Carraher University of Nebraska Lincoln s-jcarrah1@math.unl.edu Joint Work with Stephen Hartke March 2012 James Carraher (UNL) Compatible circuits in eulerian

More information

Results on edge-colored graphs and pancyclicity

Results on edge-colored graphs and pancyclicity University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln Dissertations, Theses, and Student Research Papers in Mathematics Mathematics, Department of 5-2014 Results on edge-colored

More information

Graphs. Introduction To Graphs: Exercises. Definitions:

Graphs. Introduction To Graphs: Exercises. Definitions: Graphs Eng.Jehad Aldahdooh Introduction To Graphs: Definitions: 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

More information

1 Digraphs. Definition 1

1 Digraphs. Definition 1 1 Digraphs Definition 1 Adigraphordirected graphgisatriplecomprisedofavertex set V(G), edge set E(G), and a function assigning each edge an ordered pair of vertices (tail, head); these vertices together

More information

Paths. Path is a sequence of edges that begins at a vertex of a graph and travels from vertex to vertex along edges of the graph.

Paths. Path is a sequence of edges that begins at a vertex of a graph and travels from vertex to vertex along edges of the graph. Paths Path is a sequence of edges that begins at a vertex of a graph and travels from vertex to vertex along edges of the graph. Formal Definition of a Path (Undirected) Let n be a nonnegative integer

More information

Let G = (V, E) be a graph. If u, v V, then u is adjacent to v if {u, v} E. We also use the notation u v to denote that u is adjacent to v.

Let G = (V, E) be a graph. If u, v V, then u is adjacent to v if {u, v} E. We also use the notation u v to denote that u is adjacent to v. Graph Adjacent Endpoint of an edge Incident Neighbors of a vertex Degree of a vertex Theorem Graph relation Order of a graph Size of a graph Maximum and minimum degree Let G = (V, E) be a graph. If u,

More information

GRAPHS, GRAPH MODELS, GRAPH TERMINOLOGY, AND SPECIAL TYPES OF GRAPHS

GRAPHS, GRAPH MODELS, GRAPH TERMINOLOGY, AND SPECIAL TYPES OF GRAPHS GRAPHS, GRAPH MODELS, GRAPH TERMINOLOGY, AND SPECIAL TYPES OF GRAPHS DR. ANDREW SCHWARTZ, PH.D. 10.1 Graphs and Graph Models (1) A graph G = (V, E) consists of V, a nonempty set of vertices (or nodes)

More information

Introduction to Graphs

Introduction to Graphs Introduction to Graphs Historical Motivation Seven Bridges of Königsberg Königsberg (now Kaliningrad, Russia) around 1735 Problem: Find a walk through the city that would cross each bridge once and only

More information

Graph Theory S 1 I 2 I 1 S 2 I 1 I 2

Graph Theory S 1 I 2 I 1 S 2 I 1 I 2 Graph Theory S I I S S I I S Graphs Definition A graph G is a pair consisting of a vertex set V (G), and an edge set E(G) ( ) V (G). x and y are the endpoints of edge e = {x, y}. They are called adjacent

More information

Logic: The Big Picture. Axiomatizing Arithmetic. Tautologies and Valid Arguments. Graphs and Trees

Logic: The Big Picture. Axiomatizing Arithmetic. Tautologies and Valid Arguments. Graphs and Trees Axiomatizing Arithmetic Logic: The Big Picture Suppose we restrict the domain to the natural numbers, and allow only the standard symbols of arithmetic (+,, =, >, 0, 1). Typical true formulas include:

More information

Chapter 2 Graphs. 2.1 Definition of Graphs

Chapter 2 Graphs. 2.1 Definition of Graphs Chapter 2 Graphs Abstract Graphs are discrete structures that consist of vertices and edges connecting some of these vertices. Graphs have many applications in Mathematics, Computer Science, Engineering,

More information

8.2 Paths and Cycles

8.2 Paths and Cycles 8.2 Paths and Cycles Degree a b c d e f Definition The degree of a vertex is the number of edges incident to it. A loop contributes 2 to the degree of the vertex. (G) is the maximum degree of G. δ(g) is

More information

Chapter 9 Graph Algorithms

Chapter 9 Graph Algorithms Introduction graph theory useful in practice represent many real-life problems can be if not careful with data structures Chapter 9 Graph s 2 Definitions Definitions an undirected graph is a finite set

More information

11/22/2016. Chapter 9 Graph Algorithms. Introduction. Definitions. Definitions. Definitions. Definitions

11/22/2016. Chapter 9 Graph Algorithms. Introduction. Definitions. Definitions. Definitions. Definitions Introduction Chapter 9 Graph Algorithms graph theory useful in practice represent many real-life problems can be slow if not careful with data structures 2 Definitions an undirected graph G = (V, E) is

More information

Chapter 9 Graph Algorithms

Chapter 9 Graph Algorithms Chapter 9 Graph Algorithms 2 Introduction graph theory useful in practice represent many real-life problems can be slow if not careful with data structures 3 Definitions an undirected graph G = (V, E)

More information

Characterizing Graphs (3) Characterizing Graphs (1) Characterizing Graphs (2) Characterizing Graphs (4)

Characterizing Graphs (3) Characterizing Graphs (1) Characterizing Graphs (2) Characterizing Graphs (4) S-72.2420/T-79.5203 Basic Concepts 1 S-72.2420/T-79.5203 Basic Concepts 3 Characterizing Graphs (1) Characterizing Graphs (3) Characterizing a class G by a condition P means proving the equivalence G G

More information

Graphs and trees come up everywhere. We can view the internet as a graph (in many ways) Web search views web pages as a graph

Graphs and trees come up everywhere. We can view the internet as a graph (in many ways) Web search views web pages as a graph Graphs and Trees Graphs and trees come up everywhere. We can view the internet as a graph (in many ways) who is connected to whom Web search views web pages as a graph Who points to whom Niche graphs (Ecology):

More information

Outline. Introduction. Representations of Graphs Graph Traversals. Applications. Definitions and Basic Terminologies

Outline. Introduction. Representations of Graphs Graph Traversals. Applications. Definitions and Basic Terminologies Graph Chapter 9 Outline Introduction Definitions and Basic Terminologies Representations of Graphs Graph Traversals Breadth first traversal Depth first traversal Applications Single source shortest path

More information

Chapter 9 Graph Algorithms

Chapter 9 Graph Algorithms Chapter 9 Graph Algorithms 2 Introduction graph theory useful in practice represent many real-life problems can be if not careful with data structures 3 Definitions an undirected graph G = (V, E) is a

More information

Maximum Flows of Minimum Cost

Maximum Flows of Minimum Cost Maximum Flows of Minimum Cost Figure 8-24 Two possible maximum flows for the same network Data Structures and Algorithms in Java 1 Maximum Flows of Minimum Cost (continued) Figure 8-25 Finding a maximum

More information

MATH 363 Final Wednesday, April 28. Final exam. You may use lemmas and theorems that were proven in class and on assignments unless stated otherwise.

MATH 363 Final Wednesday, April 28. Final exam. You may use lemmas and theorems that were proven in class and on assignments unless stated otherwise. Final exam This is a closed book exam. No calculators are allowed. Unless stated otherwise, justify all your steps. You may use lemmas and theorems that were proven in class and on assignments unless stated

More information

CMSC 380. Graph Terminology and Representation

CMSC 380. Graph Terminology and Representation CMSC 380 Graph Terminology and Representation GRAPH BASICS 2 Basic Graph Definitions n A graph G = (V,E) consists of a finite set of vertices, V, and a finite set of edges, E. n Each edge is a pair (v,w)

More information

V :non-empty vertex ornode set E V V :edge set G (V, E) :directed graph on V, or digraph on V

V :non-empty vertex ornode set E V V :edge set G (V, E) :directed graph on V, or digraph on V -93-11. Graph Theory Example: V :non-empty vertex ornode set E V V :edge set G (V, E) :directed graph on V, or digraph on V b e f V={a, b, c, d, e, f, g} a c d f E={(a,b), (b,c), (c,a),... } Note: (a,

More information

DEFINITION OF GRAPH GRAPH THEORY GRAPHS ACCORDING TO THEIR VERTICES AND EDGES EXAMPLE GRAPHS ACCORDING TO THEIR VERTICES AND EDGES

DEFINITION OF GRAPH GRAPH THEORY GRAPHS ACCORDING TO THEIR VERTICES AND EDGES EXAMPLE GRAPHS ACCORDING TO THEIR VERTICES AND EDGES DEFINITION OF GRAPH GRAPH THEORY Prepared by Engr. JP Timola Reference: Discrete Math by Kenneth H. Rosen A graph G = (V,E) consists of V, a nonempty set of vertices (or nodes) and E, a set of edges. Each

More information

Varying Applications (examples)

Varying Applications (examples) Graph Theory Varying Applications (examples) Computer networks Distinguish between two chemical compounds with the same molecular formula but different structures Solve shortest path problems between cities

More information

Matchings. Examples. K n,m, K n, Petersen graph, Q k ; graphs without perfect matching. A maximal matching cannot be enlarged by adding another edge.

Matchings. Examples. K n,m, K n, Petersen graph, Q k ; graphs without perfect matching. A maximal matching cannot be enlarged by adding another edge. Matchings A matching is a set of (non-loop) edges with no shared endpoints. The vertices incident to an edge of a matching M are saturated by M, the others are unsaturated. A perfect matching of G is a

More information

Eulerian Tours and Fleury s Algorithm

Eulerian Tours and Fleury s Algorithm Eulerian Tours and Fleury s Algorithm CSE21 Winter 2017, Day 12 (B00), Day 8 (A00) February 8, 2017 http://vlsicad.ucsd.edu/courses/cse21-w17 Vocabulary Path (or walk): describes a route from one vertex

More information

DS UNIT 4. Matoshri College of Engineering and Research Center Nasik Department of Computer Engineering Discrete Structutre UNIT - IV

DS UNIT 4. Matoshri College of Engineering and Research Center Nasik Department of Computer Engineering Discrete Structutre UNIT - IV Sr.No. Question Option A Option B Option C Option D 1 2 3 4 5 6 Class : S.E.Comp Which one of the following is the example of non linear data structure Let A be an adjacency matrix of a graph G. The ij

More information

Introduction III. Graphs. Motivations I. Introduction IV

Introduction III. Graphs. Motivations I. Introduction IV Introduction I Graphs Computer Science & Engineering 235: Discrete Mathematics Christopher M. Bourke cbourke@cse.unl.edu Graph theory was introduced in the 18th century by Leonhard Euler via the Königsberg

More information

Graphs. Pseudograph: multiple edges and loops allowed

Graphs. Pseudograph: multiple edges and loops allowed Graphs G = (V, E) V - set of vertices, E - set of edges Undirected graphs Simple graph: V - nonempty set of vertices, E - set of unordered pairs of distinct vertices (no multiple edges or loops) Multigraph:

More information

Institute of Operating Systems and Computer Networks Algorithms Group. Network Algorithms. Tutorial 4: Matching and other stuff

Institute of Operating Systems and Computer Networks Algorithms Group. Network Algorithms. Tutorial 4: Matching and other stuff Institute of Operating Systems and Computer Networks Algorithms Group Network Algorithms Tutorial 4: Matching and other stuff Christian Rieck Matching 2 Matching A matching M in a graph is a set of pairwise

More information

1. a graph G = (V (G), E(G)) consists of a set V (G) of vertices, and a set E(G) of edges (edges are pairs of elements of V (G))

1. a graph G = (V (G), E(G)) consists of a set V (G) of vertices, and a set E(G) of edges (edges are pairs of elements of V (G)) 10 Graphs 10.1 Graphs and Graph Models 1. a graph G = (V (G), E(G)) consists of a set V (G) of vertices, and a set E(G) of edges (edges are pairs of elements of V (G)) 2. an edge is present, say e = {u,

More information

Steiner Trees and Forests

Steiner Trees and Forests Massachusetts Institute of Technology Lecturer: Adriana Lopez 18.434: Seminar in Theoretical Computer Science March 7, 2006 Steiner Trees and Forests 1 Steiner Tree Problem Given an undirected graph G

More information

MAT 7003 : Mathematical Foundations. (for Software Engineering) J Paul Gibson, A207.

MAT 7003 : Mathematical Foundations. (for Software Engineering) J Paul Gibson, A207. MAT 7003 : Mathematical Foundations (for Software Engineering) J Paul Gibson, A207 paul.gibson@it-sudparis.eu http://www-public.it-sudparis.eu/~gibson/teaching/mat7003/ Graphs and Trees http://www-public.it-sudparis.eu/~gibson/teaching/mat7003/l2-graphsandtrees.pdf

More information

PACKING DIGRAPHS WITH DIRECTED CLOSED TRAILS

PACKING DIGRAPHS WITH DIRECTED CLOSED TRAILS PACKING DIGRAPHS WITH DIRECTED CLOSED TRAILS PAUL BALISTER Abstract It has been shown [Balister, 2001] that if n is odd and m 1,, m t are integers with m i 3 and t i=1 m i = E(K n) then K n can be decomposed

More information

Module 11. Directed Graphs. Contents

Module 11. Directed Graphs. Contents Module 11 Directed Graphs Contents 11.1 Basic concepts......................... 256 Underlying graph of a digraph................ 257 Out-degrees and in-degrees.................. 258 Isomorphism..........................

More information

Chapter 4. Relations & Graphs. 4.1 Relations. Exercises For each of the relations specified below:

Chapter 4. Relations & Graphs. 4.1 Relations. Exercises For each of the relations specified below: Chapter 4 Relations & Graphs 4.1 Relations Definition: Let A and B be sets. A relation from A to B is a subset of A B. When we have a relation from A to A we often call it a relation on A. When we have

More information

SCHOOL OF ENGINEERING & BUILT ENVIRONMENT. Mathematics. An Introduction to Graph Theory

SCHOOL OF ENGINEERING & BUILT ENVIRONMENT. Mathematics. An Introduction to Graph Theory SCHOOL OF ENGINEERING & BUILT ENVIRONMENT Mathematics An Introduction to Graph Theory. Introduction. Definitions.. Vertices and Edges... The Handshaking Lemma.. Connected Graphs... Cut-Points and Bridges.

More information

Assignment 4 Solutions of graph problems

Assignment 4 Solutions of graph problems Assignment 4 Solutions of graph problems 1. Let us assume that G is not a cycle. Consider the maximal path in the graph. Let the end points of the path be denoted as v 1, v k respectively. If either of

More information

Theory of Computing. Lecture 10 MAS 714 Hartmut Klauck

Theory of Computing. Lecture 10 MAS 714 Hartmut Klauck Theory of Computing Lecture 10 MAS 714 Hartmut Klauck Seven Bridges of Königsberg Can one take a walk that crosses each bridge exactly once? Seven Bridges of Königsberg Model as a graph Is there a path

More information

Potential Bisections of Large Degree

Potential Bisections of Large Degree Potential Bisections of Large Degree Stephen G Hartke and Tyler Seacrest Department of Mathematics, University of Nebraska, Lincoln, NE 68588-0130 {hartke,s-tseacre1}@mathunledu June 6, 010 Abstract A

More information

March 20/2003 Jayakanth Srinivasan,

March 20/2003 Jayakanth Srinivasan, Definition : A simple graph G = (V, E) consists of V, a nonempty set of vertices, and E, a set of unordered pairs of distinct elements of V called edges. Definition : In a multigraph G = (V, E) two or

More information

Definition 1.1. A matching M in a graph G is called maximal if there is no matching M in G so that M M.

Definition 1.1. A matching M in a graph G is called maximal if there is no matching M in G so that M M. 1 Matchings Before, we defined a matching as a set of edges no two of which share an end in common. Suppose that we have a set of jobs and people and we want to match as many jobs to people as we can.

More information

Lecture 4: Walks, Trails, Paths and Connectivity

Lecture 4: Walks, Trails, Paths and Connectivity Lecture 4: Walks, Trails, Paths and Connectivity Rosa Orellana Math 38 April 6, 2015 Graph Decompositions Def: A decomposition of a graph is a list of subgraphs such that each edge appears in exactly one

More information

4. (a) Draw the Petersen graph. (b) Use Kuratowski s teorem to prove that the Petersen graph is non-planar.

4. (a) Draw the Petersen graph. (b) Use Kuratowski s teorem to prove that the Petersen graph is non-planar. UPPSALA UNIVERSITET Matematiska institutionen Anders Johansson Graph Theory Frist, KandMa, IT 010 10 1 Problem sheet 4 Exam questions Solve a subset of, say, four questions to the problem session on friday.

More information

Graphs and Genetics. Outline. Computational Biology IST. Ana Teresa Freitas 2015/2016. Slides source: AED (MEEC/IST); Jones and Pevzner (book)

Graphs and Genetics. Outline. Computational Biology IST. Ana Teresa Freitas 2015/2016. Slides source: AED (MEEC/IST); Jones and Pevzner (book) raphs and enetics Computational Biology IST Ana Teresa Freitas / Slides source: AED (MEEC/IST); Jones and Pevzner (book) Outline l Motivacion l Introduction to raph Theory l Eulerian & Hamiltonian Cycle

More information

Lecture 1: Examples, connectedness, paths and cycles

Lecture 1: Examples, connectedness, paths and cycles Lecture 1: Examples, connectedness, paths and cycles Anders Johansson 2011-10-22 lör Outline The course plan Examples and applications of graphs Relations The definition of graphs as relations Connectedness,

More information

Introduction to Graphs

Introduction to Graphs Graphs Introduction to Graphs Graph Terminology Directed Graphs Special Graphs Graph Coloring Representing Graphs Connected Graphs Connected Component Reading (Epp s textbook) 10.1-10.3 1 Introduction

More information

Some Upper Bounds for Signed Star Domination Number of Graphs. S. Akbari, A. Norouzi-Fard, A. Rezaei, R. Rotabi, S. Sabour.

Some Upper Bounds for Signed Star Domination Number of Graphs. S. Akbari, A. Norouzi-Fard, A. Rezaei, R. Rotabi, S. Sabour. Some Upper Bounds for Signed Star Domination Number of Graphs S. Akbari, A. Norouzi-Fard, A. Rezaei, R. Rotabi, S. Sabour Abstract Let G be a graph with the vertex set V (G) and edge set E(G). A function

More information

Math 776 Graph Theory Lecture Note 1 Basic concepts

Math 776 Graph Theory Lecture Note 1 Basic concepts Math 776 Graph Theory Lecture Note 1 Basic concepts Lectured by Lincoln Lu Transcribed by Lincoln Lu Graph theory was founded by the great Swiss mathematician Leonhard Euler (1707-178) after he solved

More information

11.2 Eulerian Trails

11.2 Eulerian Trails 11.2 Eulerian Trails K.. onigsberg, 1736 Graph Representation A B C D Do You Remember... Definition A u v trail is a u v walk where no edge is repeated. Do You Remember... Definition A u v trail is a u

More information

Ma/CS 6a Class 8: Eulerian Cycles

Ma/CS 6a Class 8: Eulerian Cycles Ma/CS 6a Class 8: Eulerian Cycles By Adam Sheffer The Bridges of Königsberg Can we travel the city while crossing every bridge exactly once? 1 How Graph Theory was Born Leonhard Euler 1736 Eulerian Cycle

More information

CS6702 GRAPH THEORY AND APPLICATIONS QUESTION BANK

CS6702 GRAPH THEORY AND APPLICATIONS QUESTION BANK CS6702 GRAPH THEORY AND APPLICATIONS 2 MARKS QUESTIONS AND ANSWERS 1 UNIT I INTRODUCTION CS6702 GRAPH THEORY AND APPLICATIONS QUESTION BANK 1. Define Graph. 2. Define Simple graph. 3. Write few problems

More information

Proposition 1. The edges of an even graph can be split (partitioned) into cycles, no two of which have an edge in common.

Proposition 1. The edges of an even graph can be split (partitioned) into cycles, no two of which have an edge in common. Math 3116 Dr. Franz Rothe June 5, 2012 08SUM\3116_2012t1.tex Name: Use the back pages for extra space 1 Solution of Test 1.1 Eulerian graphs Proposition 1. The edges of an even graph can be split (partitioned)

More information

Theorem 2.9: nearest addition algorithm

Theorem 2.9: nearest addition algorithm There are severe limits on our ability to compute near-optimal tours It is NP-complete to decide whether a given undirected =(,)has a Hamiltonian cycle An approximation algorithm for the TSP can be used

More information

How can we lay cable at minimum cost to make every telephone reachable from every other? What is the fastest route between two given cities?

How can we lay cable at minimum cost to make every telephone reachable from every other? What is the fastest route between two given cities? 1 Introduction Graph theory is one of the most in-demand (i.e. profitable) and heavily-studied areas of applied mathematics and theoretical computer science. May graph theory questions are applied in this

More information

Fundamental Properties of Graphs

Fundamental Properties of Graphs Chapter three In many real-life situations we need to know how robust a graph that represents a certain network is, how edges or vertices can be removed without completely destroying the overall connectivity,

More information

Graphs and Trees. An example. Graphs. Example 2

Graphs and Trees. An example. Graphs. Example 2 Graphs and Trees An example How would you describe this network? What kind of model would you write for it? What kind of information would you expect to obtain? Relationship between some of the apoptotic

More information

Number Theory and Graph Theory

Number Theory and Graph Theory 1 Number Theory and Graph Theory Chapter 6 Basic concepts and definitions of graph theory By A. Satyanarayana Reddy Department of Mathematics Shiv Nadar University Uttar Pradesh, India E-mail: satya8118@gmail.com

More information

Graphs and Network Flows IE411. Lecture 21. Dr. Ted Ralphs

Graphs and Network Flows IE411. Lecture 21. Dr. Ted Ralphs Graphs and Network Flows IE411 Lecture 21 Dr. Ted Ralphs IE411 Lecture 21 1 Combinatorial Optimization and Network Flows In general, most combinatorial optimization and integer programming problems are

More information

Ma/CS 6b Class 4: Matchings in General Graphs

Ma/CS 6b Class 4: Matchings in General Graphs Ma/CS 6b Class 4: Matchings in General Graphs By Adam Sheffer Reminder: Hall's Marriage Theorem Theorem. Let G = V 1 V 2, E be a bipartite graph. There exists a matching of size V 1 in G if and only if

More information

Introduction to Graph Theory

Introduction to Graph Theory Introduction to Graph Theory Tandy Warnow January 20, 2017 Graphs Tandy Warnow Graphs A graph G = (V, E) is an object that contains a vertex set V and an edge set E. We also write V (G) to denote the vertex

More information

CS 311 Discrete Math for Computer Science Dr. William C. Bulko. Graphs

CS 311 Discrete Math for Computer Science Dr. William C. Bulko. Graphs CS 311 Discrete Math for Computer Science Dr. William C. Bulko Graphs 2014 Definitions Definition: A graph G = (V,E) consists of a nonempty set V of vertices (or nodes) and a set E of edges. Each edge

More information

Lecture 5: Graphs. Rajat Mittal. IIT Kanpur

Lecture 5: Graphs. Rajat Mittal. IIT Kanpur Lecture : Graphs Rajat Mittal IIT Kanpur Combinatorial graphs provide a natural way to model connections between different objects. They are very useful in depicting communication networks, social networks

More information

DHANALAKSHMI COLLEGE OF ENGINEERING, CHENNAI

DHANALAKSHMI COLLEGE OF ENGINEERING, CHENNAI DHANALAKSHMI COLLEGE OF ENGINEERING, CHENNAI Department of Computer Science and Engineering CS6702 - GRAPH THEORY AND APPLICATIONS Anna University 2 & 16 Mark Questions & Answers Year / Semester: IV /

More information

Lecture 5: Graphs & their Representation

Lecture 5: Graphs & their Representation Lecture 5: Graphs & their Representation Why Do We Need Graphs Graph Algorithms: Many problems can be formulated as problems on graphs and can be solved with graph algorithms. To learn those graph algorithms,

More information

0.0.1 Network Analysis

0.0.1 Network Analysis Graph Theory 0.0.1 Network Analysis Prototype Example: In Algonquian Park the rangers have set up snowmobile trails with various stops along the way. The system of trails is our Network. The main entrance

More information

2. CONNECTIVITY Connectivity

2. CONNECTIVITY Connectivity 2. CONNECTIVITY 70 2. Connectivity 2.1. Connectivity. Definition 2.1.1. (1) A path in a graph G = (V, E) is a sequence of vertices v 0, v 1, v 2,..., v n such that {v i 1, v i } is an edge of G for i =

More information

Discrete Mathematics and Probability Theory Fall 2009 Satish Rao,David Tse Note 8

Discrete Mathematics and Probability Theory Fall 2009 Satish Rao,David Tse Note 8 CS 70 Discrete Mathematics and Probability Theory Fall 2009 Satish Rao,David Tse Note 8 An Introduction to Graphs Formulating a simple, precise specification of a computational problem is often a prerequisite

More information

EECS 1028 M: Discrete Mathematics for Engineers

EECS 1028 M: Discrete Mathematics for Engineers EECS 1028 M: Discrete Mathematics for Engineers Suprakash Datta Office: LAS 3043 Course page: http://www.eecs.yorku.ca/course/1028 Also on Moodle S. Datta (York Univ.) EECS 1028 W 18 1 / 15 Graphs: Motivations

More information

Graph Theory. Connectivity, Coloring, Matching. Arjun Suresh 1. 1 GATE Overflow

Graph Theory. Connectivity, Coloring, Matching. Arjun Suresh 1. 1 GATE Overflow Graph Theory Connectivity, Coloring, Matching Arjun Suresh 1 1 GATE Overflow GO Classroom, August 2018 Thanks to Subarna/Sukanya Das for wonderful figures Arjun, Suresh (GO) Graph Theory GATE 2019 1 /

More information

context. (Similarly, we write ν for ν(g), etc. if there is no risk of confusion.) For a subset A V we write N G (A) = {v V ( w A)(v w)} (the set of

context. (Similarly, we write ν for ν(g), etc. if there is no risk of confusion.) For a subset A V we write N G (A) = {v V ( w A)(v w)} (the set of Graph Theory CMSC-27500 Spring 2015 http://people.cs.uchicago.edu/ laci/15graphs Homework set #4. First batch posted 4-9, 8am, updated 10:20am. Problems 4.16 4.31 added at 11:30pm. Due Tuesday, April 14

More information

Discrete Mathematics for CS Spring 2008 David Wagner Note 13. An Introduction to Graphs

Discrete Mathematics for CS Spring 2008 David Wagner Note 13. An Introduction to Graphs CS 70 Discrete Mathematics for CS Spring 2008 David Wagner Note 13 An Introduction to Graphs Formulating a simple, precise specification of a computational problem is often a prerequisite to writing a

More information

Graph Theory: Introduction

Graph Theory: Introduction Graph Theory: Introduction Pallab Dasgupta, Professor, Dept. of Computer Sc. and Engineering, IIT Kharagpur pallab@cse.iitkgp.ernet.in Resources Copies of slides available at: http://www.facweb.iitkgp.ernet.in/~pallab

More information

Polynomial time approximation algorithms

Polynomial time approximation algorithms Polynomial time approximation algorithms Doctoral course Optimization on graphs - Lecture 5.2 Giovanni Righini January 18 th, 2013 Approximation algorithms There are several reasons for using approximation

More information

Foundations of Discrete Mathematics

Foundations of Discrete Mathematics Foundations of Discrete Mathematics Chapter 12 By Dr. Dalia M. Gil, Ph.D. Trees Tree are useful in computer science, where they are employed in a wide range of algorithms. They are used to construct efficient

More information

Combinatorics Summary Sheet for Exam 1 Material 2019

Combinatorics Summary Sheet for Exam 1 Material 2019 Combinatorics Summary Sheet for Exam 1 Material 2019 1 Graphs Graph An ordered three-tuple (V, E, F ) where V is a set representing the vertices, E is a set representing the edges, and F is a function

More information

TWO CONTRIBUTIONS OF EULER

TWO CONTRIBUTIONS OF EULER TWO CONTRIBUTIONS OF EULER SIEMION FAJTLOWICZ. MATH 4315 Eulerian Tours. Although some mathematical problems which now can be thought of as graph-theoretical, go back to the times of Euclid, the invention

More information

Crossing bridges. Crossing bridges Great Ideas in Theoretical Computer Science. Lecture 12: Graphs I: The Basics. Königsberg (Prussia)

Crossing bridges. Crossing bridges Great Ideas in Theoretical Computer Science. Lecture 12: Graphs I: The Basics. Königsberg (Prussia) 15-251 Great Ideas in Theoretical Computer Science Lecture 12: Graphs I: The Basics February 22nd, 2018 Crossing bridges Königsberg (Prussia) Now Kaliningrad (Russia) Is there a way to walk through the

More information

Discrete mathematics II. - Graphs

Discrete mathematics II. - Graphs Emil Vatai April 25, 2018 Basic definitions Definition of an undirected graph Definition (Undirected graph) An undirected graph or (just) a graph is a triplet G = (ϕ, E, V ), where V is the set of vertices,

More information

Discrete Mathematics and Probability Theory Fall 2013 Vazirani Note 7

Discrete Mathematics and Probability Theory Fall 2013 Vazirani Note 7 CS 70 Discrete Mathematics and Probability Theory Fall 2013 Vazirani Note 7 An Introduction to Graphs A few centuries ago, residents of the city of Königsberg, Prussia were interested in a certain problem.

More information

Isomorph-free generation of 2-connected graphs with applications

Isomorph-free generation of 2-connected graphs with applications Isomorph-free generation of 2-connected graphs with applications Derrick Stolee University of Nebraska Lincoln s-dstolee1@math.unl.edu March 19, 2011 Computer Search Computers are extremely useful to graph

More information

CS200: Graphs. Prichard Ch. 14 Rosen Ch. 10. CS200 - Graphs 1

CS200: Graphs. Prichard Ch. 14 Rosen Ch. 10. CS200 - Graphs 1 CS200: Graphs Prichard Ch. 14 Rosen Ch. 10 CS200 - Graphs 1 Graphs A collection of nodes and edges What can this represent? n A computer network n Abstraction of a map n Social network CS200 - Graphs 2

More information

List of Theorems. Mat 416, Introduction to Graph Theory. Theorem 1 The numbers R(p, q) exist and for p, q 2,

List of Theorems. Mat 416, Introduction to Graph Theory. Theorem 1 The numbers R(p, q) exist and for p, q 2, List of Theorems Mat 416, Introduction to Graph Theory 1. Ramsey s Theorem for graphs 8.3.11. Theorem 1 The numbers R(p, q) exist and for p, q 2, R(p, q) R(p 1, q) + R(p, q 1). If both summands on the

More information

CPCS Discrete Structures 1

CPCS Discrete Structures 1 Let us switch to a new topic: Graphs CPCS 222 - Discrete Structures 1 Introduction to Graphs Definition: A simple graph G = (V, E) consists of V, a nonempty set of vertices, and E, a set of unordered pairs

More information

CS 441 Discrete Mathematics for CS Lecture 24. Relations IV. CS 441 Discrete mathematics for CS. Equivalence relation

CS 441 Discrete Mathematics for CS Lecture 24. Relations IV. CS 441 Discrete mathematics for CS. Equivalence relation CS 441 Discrete Mathematics for CS Lecture 24 Relations IV Milos Hauskrecht milos@cs.pitt.edu 5329 Sennott Square Equivalence relation Definition: A relation R on a set A is called an equivalence relation

More information

Modules. 6 Hamilton Graphs (4-8 lectures) Introduction Necessary conditions and sufficient conditions Exercises...

Modules. 6 Hamilton Graphs (4-8 lectures) Introduction Necessary conditions and sufficient conditions Exercises... Modules 6 Hamilton Graphs (4-8 lectures) 135 6.1 Introduction................................ 136 6.2 Necessary conditions and sufficient conditions............. 137 Exercises..................................

More information

11.4 Bipartite Multigraphs

11.4 Bipartite Multigraphs 11.4 Bipartite Multigraphs Introduction Definition A graph G is bipartite if we can partition the vertices into two disjoint subsets U and V such that every edge of G has one incident vertex in U and the

More information

Minimum Spanning Trees My T. UF

Minimum Spanning Trees My T. UF Introduction to Algorithms Minimum Spanning Trees @ UF Problem Find a low cost network connecting a set of locations Any pair of locations are connected There is no cycle Some applications: Communication

More information

Adjacent: Two distinct vertices u, v are adjacent if there is an edge with ends u, v. In this case we let uv denote such an edge.

Adjacent: Two distinct vertices u, v are adjacent if there is an edge with ends u, v. In this case we let uv denote such an edge. 1 Graph Basics What is a graph? Graph: a graph G consists of a set of vertices, denoted V (G), a set of edges, denoted E(G), and a relation called incidence so that each edge is incident with either one

More information

Algorithm Design (8) Graph Algorithms 1/2

Algorithm Design (8) Graph Algorithms 1/2 Graph Algorithm Design (8) Graph Algorithms / Graph:, : A finite set of vertices (or nodes) : A finite set of edges (or arcs or branches) each of which connect two vertices Takashi Chikayama School of

More information

Binary Relations McGraw-Hill Education

Binary Relations McGraw-Hill Education Binary Relations A binary relation R from a set A to a set B is a subset of A X B Example: Let A = {0,1,2} and B = {a,b} {(0, a), (0, b), (1,a), (2, b)} is a relation from A to B. We can also represent

More information

Graph and Digraph Glossary

Graph and Digraph Glossary 1 of 15 31.1.2004 14:45 Graph and Digraph Glossary A B C D E F G H I-J K L M N O P-Q R S T U V W-Z Acyclic Graph A graph is acyclic if it contains no cycles. Adjacency Matrix A 0-1 square matrix whose

More information

CHAPTER 14 GRAPH ALGORITHMS ORD SFO LAX DFW

CHAPTER 14 GRAPH ALGORITHMS ORD SFO LAX DFW SFO ORD CHAPTER 14 GRAPH ALGORITHMS LAX DFW ACKNOWLEDGEMENT: THESE SLIDES ARE ADAPTED FROM SLIDES PROVIDED WITH DATA STRUCTURES AND ALGORITHMS IN JAVA, GOODRICH, TAMASSIA AND GOLDWASSER (WILEY 2016) GRAPH

More information

Week 9-10: Connectivity

Week 9-10: Connectivity Week 9-0: Connectiity October 3, 206 Vertex Connectiity Let G = (V, E) be a graph. Gien two ertices x, y V. Two (x, y)-path are said to be internally disjoint if they hae no internal ertices in common.

More information

Eulerian tours. Russell Impagliazzo and Miles Jones Thanks to Janine Tiefenbruck. April 20, 2016

Eulerian tours. Russell Impagliazzo and Miles Jones Thanks to Janine Tiefenbruck.  April 20, 2016 Eulerian tours Russell Impagliazzo and Miles Jones Thanks to Janine Tiefenbruck http://cseweb.ucsd.edu/classes/sp16/cse21-bd/ April 20, 2016 Seven Bridges of Konigsberg Is there a path that crosses each

More information

4.1 Eulerian Tours. 4. Eulerian Tours and Trails. Königsberg. Seven Bridges. Try. Königsberg bridge problem

4.1 Eulerian Tours. 4. Eulerian Tours and Trails. Königsberg. Seven Bridges. Try. Königsberg bridge problem 4. Eulerian Tours and Trails 4.1 Eulerian Tours FMONG NIE 1 FMONG NIE 2 Königsberg Königsberg was a city in eastern Prussia in 18 th century. river flowed through this city and separated it into four pieces.

More information

CS473-Algorithms I. Lecture 13-A. Graphs. Cevdet Aykanat - Bilkent University Computer Engineering Department

CS473-Algorithms I. Lecture 13-A. Graphs. Cevdet Aykanat - Bilkent University Computer Engineering Department CS473-Algorithms I Lecture 3-A Graphs Graphs A directed graph (or digraph) G is a pair (V, E), where V is a finite set, and E is a binary relation on V The set V: Vertex set of G The set E: Edge set of

More information

Definition For vertices u, v V (G), the distance from u to v, denoted d(u, v), in G is the length of a shortest u, v-path. 1

Definition For vertices u, v V (G), the distance from u to v, denoted d(u, v), in G is the length of a shortest u, v-path. 1 Graph fundamentals Bipartite graph characterization Lemma. If a graph contains an odd closed walk, then it contains an odd cycle. Proof strategy: Consider a shortest closed odd walk W. If W is not a cycle,

More information