K-Coloring k-coloring: A k-coloring of a graph G is a labeling f: V(G)  S, where |S|=k. The labels are colors; the vertices of one color form a color.

Slides:



Advertisements
Similar presentations
Great Theoretical Ideas in Computer Science
Advertisements

Coloring Warm-Up. A graph is 2-colorable iff it has no odd length cycles 1: If G has an odd-length cycle then G is not 2- colorable Proof: Let v 0, …,
Connectivity - Menger’s Theorem Graphs & Algorithms Lecture 3.
Lecture 5 Graph Theory. Graphs Graphs are the most useful model with computer science such as logical design, formal languages, communication network,
 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.
Graph Coloring prepared and Instructed by Shmuel Wimer Eng. Faculty, Bar-Ilan University March 2014Graph Coloring1.
Edge-Coloring of Graphs On the left we see a 1- factorization of  5, the five-sided prism. Each factor is respresented by its own color. No edges of the.
Chapter 9 Connectivity 连通度. 9.1 Connectivity Consider the following graphs:  G 1 : Deleting any edge makes it disconnected.  G 2 : Cannot be disconnected.
GOLOMB RULERS AND GRACEFUL GRAPHS
Applied Combinatorics, 4th Ed. Alan Tucker
Last time: terminology reminder w Simple graph Vertex = node Edge Degree Weight Neighbours Complete Dual Bipartite Planar Cycle Tree Path Circuit Components.
1 Discrete Structures & Algorithms Graphs and Trees: II EECE 320.
k-Factor Factor: a spanning subgraph of graph G
Vertex Cut Vertex Cut: A separating set or vertex cut of a graph G is a set S  V(G) such that G-S has more than one component. a b c d e f g h i.
Connectivity and Paths
Graph. Undirected Graph Directed Graph Simple Graph.
Mycielski’s Construction Mycielski’s Construction: From a simple graph G, Mycielski’s Construction produces a simple graph G’ containing G. Beginning with.
Internally Disjoint Paths Internally Disjoint Paths : Two paths u to v are internally disjoint if they have no common internal vertex.
Graph Theory Ming-Jer Tsai. Outline Graph Graph Theory Grades Q & A.
Vertex Cut Vertex Cut: A separating set or vertex cut of a graph G is a set SV(G) such that S has more than one component. Connectivity of G ((G)): The.
Definition Dual Graph G* of a Plane Graph:
Counting Proper Colors Given k  N and a graph G, the value  (G;k) is the number of proper colorings f: V(G)  [k], where the k colors need not all be.
Counting Proper Colors Given k  N and a graph G, the value  (G;k) is the number of proper colorings f: V(G)  [k]. The set of available colors is [k]={1,…,k};
Factor Factor: a spanning subgraph of graph G
Coloring Algorithms and Networks. Coloring2 Graph coloring Vertex coloring: –Function f: V  C, such that for all {v,w}  E: f(v)  f(w) Chromatic number.
Factor Factor: a spanning subgraph of graph G k-Factor: a spanning k-regular subgraph Odd component: a component of odd order o(H): the number of odd components.
Graph Theory Ch.5. Coloring of Graphs 1 Chapter 5 Coloring of Graphs.
Internally Disjoint Paths Internally Disjoint Paths : Two paths u to v are internally disjoint if they have no common internal vertex. u u v v Common internal.
Vertex Cut Vertex Cut: A separating set or vertex cut of a graph G is a set SV(G) such that G-S has more than one component. d f b e a g c i h.
K-Coloring k-coloring: A k-coloring of a graph G is a labeling f: V(G)  S, where |S|=k. The labels are colors; the vertices of one color form a color.
Minimum Spanning Trees. Subgraph A graph G is a subgraph of graph H if –The vertices of G are a subset of the vertices of H, and –The edges of G are a.
Graph Coloring.
9.2 Graph Terminology and Special Types Graphs
 Jim has six children.  Chris fights with Bob,Faye, and Eve all the time; Eve fights (besides with Chris) with Al and Di all the time; and Al and Bob.
Trees and Distance. 2.1 Basic properties Acyclic : a graph with no cycle Forest : acyclic graph Tree : connected acyclic graph Leaf : a vertex of degree.
CSE, IIT KGP Graph Theory: Introduction Pallab Dasgupta Dept. of CSE, IIT
Chapter 1 Fundamental Concepts II Pao-Lien Lai 1.
The Equitable Coloring of Kneser Graphs 陳伯亮 & 黃國卿 2008 年 8 月 11 日.
1 CS104 : Discrete Structures Chapter V Graph Theory.
Indian Institute of Technology Kharagpur PALLAB DASGUPTA Graph Theory: Introduction Pallab Dasgupta, Professor, Dept. of Computer Sc. and Engineering,
Mycielski’s Construction Mycielski’s Construction: From a simple graph G, Mycielski’s Construction produces a simple graph G’ containing G. Beginning with.
5.2 Trees  A tree is a connected graph without any cycles.
The Equitable Colorings of Kneser Graphs Kuo-Ching Huang ( 黃國卿 ) Department of Applied Mathematics Providence University This is a joined work with Prof.
Chapter 5 Coloring of Graphs. 5.1 Vertex Coloring and Upper Bound Definition: A k-coloring of a graph G is a labeling f:V(G)  S, where |S|=k (or S=[k]).
Chapter 1 Fundamental Concepts Introduction to Graph Theory Douglas B. West July 11, 2002.
CSE, IIT KGP Graph Coloring. CSE, IIT KGP K-coloring A k-coloring of G is a labeling f:V(G)  {1,…,k}.A k-coloring of G is a labeling f:V(G)  {1,…,k}.
Connectivity and Paths 報告人:林清池. Connectivity A separating set of a graph G is a set such that G-S has more than one component. The connectivity of G,
Unit – V Graph theory. Representation of Graphs Graph G (V, E,  ) V Set of vertices ESet of edges  Function that assigns vertices {v, w} to each edge.
Graph Theory and Applications
Chap. 11 Graph Theory and Applications 1. Directed Graph 2.
Trees Thm 2.1. (Cayley 1889) There are nn-2 different labeled trees
Graphs Lecture 2. Graphs (1) An undirected graph is a triple (V, E, Y), where V and E are finite sets and Y:E g{X V :| X |=2}. A directed graph or digraph.
Introduction to Graph Theory
Introduction to Graph Theory
Graph Theory Ming-Jer Tsai. Outline Graph Graph Theory Grades Q & A.
CSE, IIT KGP Graph Theory: Introduction Pallab Dasgupta Dept. of CSE, IIT
 Hamilton paths.  Definition 20: A Hamilton paths is a path that contains each vertex exactly once. A Hamilton circuit is a circuit that contains.
Chromatic Coloring with a Maximum Color Class Bor-Liang Chen Kuo-Ching Huang Chih-Hung Yen* 30 July, 2009.
Trees.
Graph Coloring.
Proof technique (pigeonhole principle)
Graph theory Definitions Trees, cycles, directed graphs.
Planarity Testing.
Discrete Math II Howon Kim
Graph Coloring.
Proof Techniques.
Miniconference on the Mathematics of Computation
Winter 2019 Lecture 11 Minimum Spanning Trees (Part II)
Graph Theory: Cuts and Connectivity
Autumn 2019 Lecture 11 Minimum Spanning Trees (Part II)
Presentation transcript:

k-Coloring k-coloring: A k-coloring of a graph G is a labeling f: V(G)  S, where |S|=k. The labels are colors; the vertices of one color form a color class. Proper k-coloring: A k-coloring is proper if adjacent vertices have different labels. k-colorable graph: A graph is k-colorable if it has a proper k-coloring. Chromatic number  (G): The least k such that G is k-colorable.

Example Petersen Graph: The Petersen graph is the simple graph whose vertices are the 2-element subsets of a 5- element set and whose edges are the pairs of disjoint 2-element subsets. A graph is 2-colorable if and only if it is bipartite.  C5 and Petersen graph have chromatic number at least 3.

k-chromatic graph k-chromatic graph : A graph G is k-chromatic if  (G)=k. A proper k-coloring of a k-chromatic graph is an optimal coloring. k-critical graph : If  (H)<  (G)=k for every proper subgraph H of G, then G is k-critical. Clique Number: The clique number of a graph G, written  (G), is the maximum size of clique in G.

Proposition For any graph G,  (G)>=  (G) and  (G)<=n(G)/  (G). Proof. 1. Vertices of a clique requires distinct colors.   (G)>=  (G). 2. Each color class is an independent set.   (G)<=n(G)/  (G).

Example of  (G)>  (G) 1. For r>=2, let G=C 2r+1  K s. 2. C 2r+1 has no triangle   (G)=s C 2r+1 needs at least three colors, say a, b, and c. 4. K s needs s colors which must differ from colors a, b, and c.   (G)>=s+3.

Greedy Coloring The greedy algorithm relative to a vertex ordering v 1, v 2, …, v n of V(G) is obtained by coloring vertices in the order v 1, v 2, …, v n, assigning to v i the smallest- indexed color not already used on its lower-indexed neighbors.

Proposition  (G)<=  (G)+1. Proof. 1. In a vertex ordering, each vertex has at most  (G) earlier neighbors.  Greedy coloring cannot be forced to use more than  (G)+1 colors.

Brook’s Theorem If G is a connected graph other than a complete graph or an odd cycle, then  (G)<=  (G). Proof. 1. Let k=  (G). 2. Since G is a complete graph when k =3. 3. The theorem holds if we can order the vertices such that each has at most k-1 lower-indexed neighbors.

Brook’s Theorem (2/6) 4. Case 1: G is not k-regular. Let v n be the vertex of degree less than k. 5. Grow a spanning tree of G from v n, assigning indices in decreasing order as we reach vertices. 6. Each vertex other than v n in the resulting ordering has v 1, v 2, …, v n has a higher-indexed neighbor along the path to v n in the tree.  Each vertex has at most k-1 lower-indexed neighbors.

Brook’s Theorem (3/6) 4. Case 2: G is k-regular. 5. Case 2-1: G has a cut-vertex x. 6. Let G’ be a subgraph consisting of a component of G- x together with its edges to x. 7. The degree of x in G’ is less than k.  The method in case 1 provides a proper k-coloring of G’. 8. By permuting the names of colors in the subgraphs resulting in this way from components of G-x, we can make the colorings agree on x to complete a proper k- coloring of G.

Brook’s Theorem (4/6) 9. Case 2-2: G is 2-connected. 10. Suppose that some vertex v n has neighbors v 1, v 2 such that (v 1, v 2 )  E(G) and G-{v 1, v 2 } is connected. 11. Index the vertices of a spanning tree of G-{v 1, v 2 } using 3, 4, …, n such that labels increase along paths to the root v n. 12. Each of v 1, v 2, …, v n has at most k-1 lower indexed neighbors. 13. v 1 and v 2 receives the same color.  At most k-1 colors are used on neighbors of v n.

Brook’s Theorem (5/6) 14. It suffices to show that every 2-connected k-regular graph with k>=3 has such a triple v 1, v 2, v n in Choose a vertex x. 16. Case 2-2-1:  (G-x)>= Let v 1 be x and let v 2 be a vertex with distance 2 from x. 18. Let v n be a common neighbor of v 1 and v v 1, v 2, v n be the desired triple. 20. Case 2-2-2:  (G-x)=1.

Brook’s Theorem (6/6) 21. Let v n =x. Then, x has a neighbor in every leaf block of G-x. Otherwise, G is not 2-connected. 22. G-x is not a single block.  At least two leaf blocks in G-x. 23. Clearly, neighbors v 1 and v 2 of x are not adjacent. 24. G-{v 1, v 2, x} is connected since blocks have no cut- vertices. 25. k>=3.  vertex x has a neighbor other than v 1 and v 2  G-{v 1, v 2 } is connected.

Block-cutpoint graph Block-cutpoint graph: The block-cutpoint graph of a graph G is a bipartite graph H in which one partite set consists of the cut-vertices of G, and the other has a vertex b i for each block B i of G. vb i as an edge of H if and only if v  B i.

Leaf Block Leaf Block: A block that contains exactly one cut- vertex of G. When G is connected, its block-cutpoint graph is a tree (Exercise 34 of Sec. 4.1) whose leaves are blocks of G.  A single block has at least two leaf blocks.