Shortest Path Based Sufficiency Condition for Hamiltonian Graphs

Slides:



Advertisements
Similar presentations
CSE 211 Discrete Mathematics
Advertisements

CS 336 March 19, 2012 Tandy Warnow.
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, …,
 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,
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,
Walks, Paths and Circuits Walks, Paths and Circuits Sanjay Jain, Lecturer, School of Computing.
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.
1 Lecture 5 (part 2) Graphs II Euler and Hamiltonian Path / Circuit Reading: Epp Chp 11.2, 11.3.
9.2 The Traveling Salesman Problem. Let us return to the question of finding a cheapest possible cycle through all the given towns: We have n towns (points)
Complexity 11-1 Complexity Andrei Bulatov NP-Completeness.
Section 2.1 Euler Cycles Vocabulary CYCLE – a sequence of consecutively linked edges (x 1,x2),(x2,x3),…,(x n-1,x n ) whose starting vertex is the ending.
What is the first line of the proof? a). Assume G has an Eulerian circuit. b). Assume every vertex has even degree. c). Let v be any vertex in G. d). Let.
Definition Hamiltonian graph: A graph with a spanning cycle (also called a Hamiltonian cycle). Hamiltonian graph Hamiltonian cycle.
An Euler Circuit is a cycle of an undirected graph, that traverses every edge of the graph exactly once, and ends at the same node from which it began.
Computability and Complexity 16-1 Computability and Complexity Andrei Bulatov NP-Completeness.
1 CIS /204—Spring 2008 Recitation 10 Friday, April 4, 2008.
Math Foundations Week 12 Graphs (2). Agenda Paths Connectivity Euler paths Hamilton paths 2.
Is the following graph Hamiltonian- connected from vertex v? a). Yes b). No c). I have absolutely no idea v.
4/17/2017 Section 8.5 Euler & Hamilton Paths ch8.5.
Complexity ©D.Moshkovitz 1 Paths On the Reasonability of Finding Paths in Graphs.
Introduction to Graph Theory
GRAPH Learning Outcomes Students should be able to:
Turan’s theorem and extremal graphs Question: How many edges a simple graph must have to guarantee that the graph contains a triangle? Since K m,m and.
MCS 312: NP Completeness and Approximation algorithms Instructor Neelima Gupta
Constructing Hamiltonian Circuits When all nodes have degree of at least n/2 (Also: an implementation in C++ using Boost) Presented by Alan SUnMaRC,
An Improved Degree Based Condition for Hamiltonian Cycles November 22, 2005 November 22, 2005.
Hamiltonian Graphs By: Matt Connor Fall 2013.
CSE 20: Discrete Mathematics for Computer Science Prof. Shachar Lovett.
CSNB143 – Discrete Structure Topic 9 – Graph. Learning Outcomes Student should be able to identify graphs and its components. Students should know how.
CS 200 Algorithms and Data Structures
Fall 2015 COMP 2300 Discrete Structures for Computation Donghyun (David) Kim Department of Mathematics and Physics North Carolina Central University 1.
A study of k-ordered hamiltonian graphs. Story begins L. Ng, M. Schultz, k-Ordered Hamiltonian graphs, J. Graph Theory 24 (1997) 45–57.
10. Lecture WS 2014/15 Bioinformatics III1 V10 Metabolic networks - Graph connectivity Graph connectivity is related to analyzing biological networks for.
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.
Eulerian Paths and Cycles. What is a Eulerian Path Given an graph. Find a path which uses every edge exactly once. This path is called an Eulerian Path.
Lecture 52 Section 11.2 Wed, Apr 26, 2006
Walks, Paths and Circuits. A graph is a connected graph if it is possible to travel from one vertex to any other vertex by moving along successive edges.
Introduction to Graph Theory
Chapter 11 - Graph CSNB 143 Discrete Mathematical Structures.
Introduction to Graph Theory
1) Find and label the degree of each vertex in the graph.
Graphs Definition: a graph is an abstract representation of a set of objects where some pairs of the objects are connected by links. The interconnected.
12. Lecture WS 2012/13Bioinformatics III1 V12 Menger’s theorem Borrowing terminology from operations research consider certain primal-dual pairs of optimization.
Approximation Algorithms by bounding the OPT Instructor Neelima Gupta
Grade 11 AP Mathematics Graph Theory Definition: A graph, G, is a set of vertices v(G) = {v 1, v 2, v 3, …, v n } and edges e(G) = {v i v j where 1 ≤ i,
1 Lecture 5 (part 2) Graphs II (a) Circuits; (b) Representation Reading: Epp Chp 11.2, 11.3
Trees.
An Introduction to Graph Theory
Hamiltonian Graphs Graphs Hubert Chan (Chapter 9.5)
Euler and Hamiltonian Graphs
Graph theory Definitions Trees, cycles, directed graphs.
Discrete Structures – CNS2300
Hamiltonian Graphs Graphs Hubert Chan (Chapter 9.5)
CSE 20: Discrete Mathematics for Computer Science Prof. Shachar Lovett
Spanning Trees Discrete Mathematics.
Can you draw this picture without lifting up your pen/pencil?
V17 Metabolic networks - Graph connectivity
Connectivity Section 10.4.
V11 Metabolic networks - Graph connectivity
Hamiltonian Cycles.
Euler and Hamilton Paths
V12 Menger’s theorem Borrowing terminology from operations research
V11 Metabolic networks - Graph connectivity
Applied Combinatorics, 4th Ed. Alan Tucker
Warm Up – Tuesday Find the critical times for each vertex.
Warm Up – 3/19 - Wednesday Give the vertex set. Give the edge set.
V11 Metabolic networks - Graph connectivity
Presentation transcript:

Shortest Path Based Sufficiency Condition for Hamiltonian Graphs Tanvir Kaykobad

Hamiltonian Graph A Hamiltonian Path is a path that traverses through each vertex of a graph exactly once A Hamiltonian Cycle is a cycle that visits every vertex of the graph exactly once A graph is Hamiltonian if it contains a Hamiltonian Cycle Finding whether a graph is Hamiltonian is an NP-complete problem.

Existing Sufficiency Conditions for Hamiltonicity Let be the degree of vertex u of a Graph and or be the distance between the vertices and . Let be a path of length (having vertices) from vertex to vertex . Dirac’s Condition: In a simple graph, if for every vertex, then the graph is Hamiltonian Ore’s Condition: In a simple graph, if for every nonadjacent pair then the graph is Hamiltonian Rahman and Kaykobad: If for every nonadjacent pair of vertices of a simple graph , then the graph contains a Hamiltonian path.

Our Proposition A graph is if there does not exist a set of vertices, whose removal disconnects the graph. If a graph is not , it cannot be Hamiltonian If for all non-adjacent vertices and of a simple graph , then the graph is Hamiltonian

Cross-over edge In a given path P with vertices indexed from left to right, if there is an intermediate vertex k such that k is connected to the leftmost vertex and its previous vertex (k-1) is connect to the rightmost vertex then these two edges are called edges cross-over edges. If cross-over edges exist in a path, then a cycle can be created with all the vertices in the path.

Maximal Path A maximal path is a non-extendable path that cannot be included in any cycle other than a Hamiltonian cycle. Start with a single edge path If crossover edges are found, the path forms a cycle, If there are any other vertices on the graph, we connect it to our cycle and remove one edge from the connecting vertex on the cycle to form our new path. Extend the path on any side without revisiting the same vertex If Step 3 is no longer possible and if the two ends of the path are adjacent, then it will form a cycle. We extend this cycle to a larger path. When step 2, 3 and 4 are no longer viable, we have obtained our maximal path

Maximal Path Example

Maximal Path Example

Maximal Path Example

Maximal Path Example

Maximal Path Example

Maximal Path Example

Maximal Path Example

Hamiltonicity Given a simple 2-connected graph let P be a maximal path with i and j as the end vertices. We will prove that if then the graph is hamiltonian. We will cover our proof using 4 cases

Case Since P is a maximal path, it cannot be included in any cycle other than a Hamiltonian cycle. So let us assume that there is no cross-over edges. If vertex i is connected to vertex k then vertex j cannot be connected to vertex . Now, since i is connected to vertices, Hypothesis of the theorem asserts that Hence . . That is . So P must be a Hamiltonian path. Thus if end vertices of a maximal path satisfies the hypothesis of the theorem, it must be a Hamiltonian path.

Case Case Let k be the rightmost vertex, vertex i is connected then all vertices to the left of k must also be connected to i and not to j. Similar argument will lead to all vertices to the right of k will be connected to j. Since , vertex j must also be connected to k. Now since the graph is 2-connected, vertex k cannot be a cut vertex. Therefore, there exists an edge with q to the left of k and s to the right. This will lead to the following cycle: which is Hamiltonian. This case gives us an improvement on Ore’s condition

Case In this case Then and cannot be connected and there is no vertex because then the path length will be shorter and can be adjacent to at most vertices. That is . So , which means P is a Hamiltonian path

Case Since each vertex on path is adjacent to either i or j and not both, to deny crossover edges the path can be partitioned by vertex k such that all vertices up to are connected to i, and the rest are connected to j. This makes and k cut vertices Now since the graph is 2-connected, vertex k cannot be a cut vertex. Therefore, there exists an edge (q,s) with q to the left of k-1 and s to the right of k. Which is Hamiltonian OR there exist two edges (q,k-1) and (k,s). First being a bridge for vertex (k-1) and the second for k2.

Case If A: This will lead to the following cycle: If B: This will lead to the following cycle: Therefore this must be a Hamiltonian cycle

Case Let the intermediate vertices on the shortest path be where . Since vertices neighbouring to can neither be connected to i nor to j they must be vertices on the shortest path. Vertices with index must be connected to i. The vertices with index in the same way should be connected to j. Nonadjacent vertices of the shortest path cannot be connected since then the shortest path will be shorter. In order that none of the vertices be cut vertices we must have an edge connecting vertices with index <i1 to a vertex indexed ik-2 in which case again the path length will be shorter (in fact only 3!). Thus this case cannot arise.

Bibleography Dirac, G. A. (1952), "Some theorems on abstract graphs", Proceedings of the London Mathematical Society, 3rd Ser. 2: 69–81 Ore, Ø. (1960), "Note on Hamilton circuits", American Mathematical Monthly 67 (1): 55 Mohammad Sohel Rahman and M Kaykobad and Mohammad Saifur Rahman, “A New Sufficient Condition for the Existence of Hamiltonian Paths”, Computers and Their Applications, pp. 56-59, ISCA, 2005