Information about Graph Theory
In mathematics and computer science, graph theory is the study of graphs; mathematical structures used to model pairwise relations between objects from a certain collection. A "graph" in this context refers to a collection of vertices or 'nodes' and a collection of edges that connect pairs of vertices. A graph may be undirected, meaning that there is no distinction between the two vertices associated with each edge, or its edges may be directed from one vertex to another; see graph (mathematics) for more detailed definitions and for other variations in the types of graphs that are commonly considered. The graphs studied in graph theory should not be confused with "graphs of functions" and other kinds of graphs.
More than one century after Euler's paper on the bridges of Königsberg and while Listing introduced topology, Cayley was led by the study of particular analytical forms arising from differential calculus to study a particular class of graphs, the trees. This study had many implications in theoretical chemistry. The involved techniques mainly concerned the enumeration of graphs having particular properties. Enumerative graph theory then rose from the results of Cayley and the fundamental results published by Pólya between 1935 and 1937 and the generalization of these by De Bruijn in 1959. Cayley linked his results on trees with the contemporary studies of chemical composition[4]. The fusion of the ideas coming from mathematics with those coming from chemistry is at the origin of a part of the standard terminology of graph theory. In particular, the term graph was introduced by Sylvester in a paper published in 1878 in Nature[5].
One of the most famous and productive problems of graph theory is the four color problem: "Is it true that any map drawn in the plane may have its regions colored with four colors, in such a way that any two regions having a common border have different colors?". This problem remained unsolved for more than a century and the proof given by Kenneth Appel and Wolfgang Haken in 1976[6][7] (determination of 1936 types of configurations of which study is sufficient and checking of the properties of these configurations by computer) did not convince all the community. A simpler proof considering far fewer configurations was given twenty years later by Robertson, Seymour, Sanders and Thomas[8].
This problem was first posed by Francis Guthrie in 1852 and the first written record of this problem is a letter of De Morgan addressed to Hamilton the same year. Many incorrect proofs have been proposed, including those by Cayley, Kempe, and others. The study and the generalization of this problem by Tait, Heawood, Ramsey and Hadwiger has in particular led to the study of the colorings of the graphs embedded on surfaces with arbitrary genus. Tait's reformulation generated a new class of problems, the factorization problems, particularly studied by Petersen and Kőnig. The works of Ramsey on colorations and more specially the results obtained by Turán in 1941 is at the origin of another branch of graph theory, the extremal graph theory.
The autonomous development of topology from 1860 and 1930 fertilized graph theory back through the works of Jordan, Kuratowski and Whitney. Another important factor of common development of graph theory and topology came from the use of the techniques of modern algebra. The first example of such a use comes from the work of the physicist Gustav Kirchhoff, who published in 1845 his Kirchhoff's circuit laws for calculating the voltage and current in electric circuits.
The introduction of probabilistic methods in graph theory, especially in the study of Erdős and Rényi of the asymptotic probability of graph connectivity, gave rise to yet another branch, known as random graph theory, which has been a fruitful source of graph-theoretic results.
Graphs are represented graphically by drawing a dot for every vertex, and drawing an arc between two vertices if they are connected by an edge. If the graph is directed, the direction is indicated by drawing an arrow.
A graph drawing should not be confused with the graph itself (the abstract, non-graphical structure) as there are several ways to structure the graph drawing. All that matters is which vertices are connected to which others by how many edges and not the exact layout. In practice it is often difficult to decide if two drawings represent the same graph. Depending on the problem domain some layouts may be better suited and easier to understand than others.
There are different ways to store graphs in a computer system. The data structure used depends on both the graph structure and the algorithm used for manipulating the graph. Theoretically one can distinguish between list and matrix structures but in concrete applications the best structure is often a combination of both. List structures are often preferred for sparse graphs as they have smaller memory requirements. Matrix structures on the other hand provide faster access for some applications but can consume huge amounts of memory .
Structures that can be represented as graphs are ubiquitous, and many problems of practical interest can be represented by graphs. The link structure of a website could be represented by a directed graph: the vertices are the web pages available at the website and a directed edge from page A to page B exists if and only if A contains a link to B. A similar approach can be taken to problems in travel, biology, computer chip design, and many other fields. The development of algorithms to handle graphs is therefore of major interest in computer science.
A graph structure can be extended by assigning a weight to each edge of the graph. Graphs with weights, or weighted graphs, are used to represent structures in which pairwise connections have some numerical values. For example if a graph represents a road network, the weights could represent the length of each road. A digraph with weighted edges in the context of graph theory is called a network.
Networks have many uses in the practical side of graph theory, network analysis (for example, to model and analyze traffic networks). Within network analysis, the definition of the term "network" varies, and may often refer to a simple graph.
Many applications of graph theory exist in the form of network analysis. These split broadly into two categories. Firstly, analysis to determine structural properties of a network, such as the distribution of vertex degrees and the diameter of the graph. A vast number of graph measures exist, and the production of useful ones for various domains remains an active area of research. Secondly, analysis to find a measurable quantity within the network, for example, for a transportation network, the level of vehicular flow within any portion of it.
Graph theory is also used to study molecules in chemistry and physics. In condensed matter physics, the three dimensional structure of complicated simulated atomic structures can be studied quantitatively by gathering statistics on graph-theoretic properties related to the topology of the atoms. For example, Franzblau's shortest-path (SP) rings. In chemistry a graph makes a natural model for a molecule, where vertices represent atoms and edges bonds. This approach is especially used in computer processing of molecular structures, ranging from chemical editors to database searching.
Graph theory is also widely used in sociology as a way, for example, to measure actors' prestige or to explore diffusion mechanisms, notably through the use of social network analysis software.
History
The paper written by Leonhard Euler on the Seven Bridges of Königsberg and published in 1736 is regarded as the first paper in the history of graph theory[1]. This paper, as well as the one written by Vandermonde on the knight problem carried on with the analysis situs initiated by Leibniz. Euler's formula relating the number of edges, vertices, and faces of a convex polyhedron was studied and generalized by Cauchy[2] and L'Huillier[3], and is at the origin of topology.More than one century after Euler's paper on the bridges of Königsberg and while Listing introduced topology, Cayley was led by the study of particular analytical forms arising from differential calculus to study a particular class of graphs, the trees. This study had many implications in theoretical chemistry. The involved techniques mainly concerned the enumeration of graphs having particular properties. Enumerative graph theory then rose from the results of Cayley and the fundamental results published by Pólya between 1935 and 1937 and the generalization of these by De Bruijn in 1959. Cayley linked his results on trees with the contemporary studies of chemical composition[4]. The fusion of the ideas coming from mathematics with those coming from chemistry is at the origin of a part of the standard terminology of graph theory. In particular, the term graph was introduced by Sylvester in a paper published in 1878 in Nature[5].
One of the most famous and productive problems of graph theory is the four color problem: "Is it true that any map drawn in the plane may have its regions colored with four colors, in such a way that any two regions having a common border have different colors?". This problem remained unsolved for more than a century and the proof given by Kenneth Appel and Wolfgang Haken in 1976[6][7] (determination of 1936 types of configurations of which study is sufficient and checking of the properties of these configurations by computer) did not convince all the community. A simpler proof considering far fewer configurations was given twenty years later by Robertson, Seymour, Sanders and Thomas[8].
This problem was first posed by Francis Guthrie in 1852 and the first written record of this problem is a letter of De Morgan addressed to Hamilton the same year. Many incorrect proofs have been proposed, including those by Cayley, Kempe, and others. The study and the generalization of this problem by Tait, Heawood, Ramsey and Hadwiger has in particular led to the study of the colorings of the graphs embedded on surfaces with arbitrary genus. Tait's reformulation generated a new class of problems, the factorization problems, particularly studied by Petersen and Kőnig. The works of Ramsey on colorations and more specially the results obtained by Turán in 1941 is at the origin of another branch of graph theory, the extremal graph theory.
The autonomous development of topology from 1860 and 1930 fertilized graph theory back through the works of Jordan, Kuratowski and Whitney. Another important factor of common development of graph theory and topology came from the use of the techniques of modern algebra. The first example of such a use comes from the work of the physicist Gustav Kirchhoff, who published in 1845 his Kirchhoff's circuit laws for calculating the voltage and current in electric circuits.
The introduction of probabilistic methods in graph theory, especially in the study of Erdős and Rényi of the asymptotic probability of graph connectivity, gave rise to yet another branch, known as random graph theory, which has been a fruitful source of graph-theoretic results.
Drawing graphs
Graphs are represented graphically by drawing a dot for every vertex, and drawing an arc between two vertices if they are connected by an edge. If the graph is directed, the direction is indicated by drawing an arrow.
A graph drawing should not be confused with the graph itself (the abstract, non-graphical structure) as there are several ways to structure the graph drawing. All that matters is which vertices are connected to which others by how many edges and not the exact layout. In practice it is often difficult to decide if two drawings represent the same graph. Depending on the problem domain some layouts may be better suited and easier to understand than others.
Graph-theoretic data structures
There are different ways to store graphs in a computer system. The data structure used depends on both the graph structure and the algorithm used for manipulating the graph. Theoretically one can distinguish between list and matrix structures but in concrete applications the best structure is often a combination of both. List structures are often preferred for sparse graphs as they have smaller memory requirements. Matrix structures on the other hand provide faster access for some applications but can consume huge amounts of memory .
List structures
- Incidence list - The edges are represented by an array containing pairs (ordered if directed) of vertices (that the edge connects) and possibly weight and other data.
- Adjacency list - Much like the incidence list, each vertex has a list of which vertices it is adjacent to. This causes redundancy in an undirected graph: for example, if vertices A and B are adjacent, A's adjacency list contains B, while B's list contains A. Adjacency queries are faster, at the cost of extra storage space.
Matrix structures
- Incidence matrix - The graph is represented by a matrix of E (edges) by V (vertices), where [edge, vertex] contains the edge's data (simplest case: 1 - connected, 0 - not connected).
- Adjacency matrix - there is an N by N matrix, where N is the number of vertices in the graph. If there is an edge from some vertex x to some vertex y, then the element
is 1, otherwise it is 0. This makes it easier to find subgraphs, and to reverse graphs if needed.
- Laplacian matrix or Kirchhoff matrix or Admittance matrix - is defined as degree matrix minus adjacency matrix and thus contains adjacency information and degree information about the vertices
- Distance matrix - A symmetric N by N matrix an element of which is the length of shortest path between x and y; if there is no such path = infinity. It can be derived from powers of the Adjacency matrix.
Problems in graph theory
Enumeration
There is a large literature on graphical enumeration: the problem of counting graphs meeting specified conditions. Some of this work is found in Harary and Palmer (1973).Subgraphs, induced subgraphs, and minors
A common problem, called the subgraph isomorphism problem, is finding a fixed graph as a subgraph in a given graph. One reason to be interested in such a question is that many graph properties are hereditary for subgraphs, which means that a graph has the property if and only if all subgraphs, or all induced subgraphs, have it too. Unfortunately, finding maximal subgraphs of a certain kind is often an NP-complete problem.- Finding the largest complete graph is called the clique problem (NP-complete).
- Finding the largest edgeless induced subgraph, or independent set, called the independent set problem (NP-complete).
- A graph is planar if it contains as a minor neither the complete bipartite graph
(See the Three cottage problem) nor the complete graph 
.
Graph coloring
Many problems have to do with various ways of coloring graphs, for example:- The four-color theorem
- The strong perfect graph theorem
- The Erdős-Faber-Lovász conjecture (unsolved)
- The total coloring conjecture (unsolved)
- The list coloring conjecture (unsolved)
Route problems
- Hamiltonian path and cycle problems
- Minimum spanning tree
- Route inspection problem (also called the "Chinese Postman Problem")
- Seven Bridges of Königsberg
- Shortest path problem
- Steiner tree
- Three cottage problem
- Traveling salesman problem (NP-Complete)
Network flow
There are numerous problems arising especially from applications that have to do with various notions of flows in networks, for example:Visibility graph problems
Covering problems
Covering problems are specific instances of subgraph-finding problems, and they tend to be closely related to the clique problem or the independent set problem.Applications
Applications of graph theory are primarily, but not exclusively, concerned with labeled graphs and various specializations of these.Structures that can be represented as graphs are ubiquitous, and many problems of practical interest can be represented by graphs. The link structure of a website could be represented by a directed graph: the vertices are the web pages available at the website and a directed edge from page A to page B exists if and only if A contains a link to B. A similar approach can be taken to problems in travel, biology, computer chip design, and many other fields. The development of algorithms to handle graphs is therefore of major interest in computer science.
A graph structure can be extended by assigning a weight to each edge of the graph. Graphs with weights, or weighted graphs, are used to represent structures in which pairwise connections have some numerical values. For example if a graph represents a road network, the weights could represent the length of each road. A digraph with weighted edges in the context of graph theory is called a network.
Networks have many uses in the practical side of graph theory, network analysis (for example, to model and analyze traffic networks). Within network analysis, the definition of the term "network" varies, and may often refer to a simple graph.
Many applications of graph theory exist in the form of network analysis. These split broadly into two categories. Firstly, analysis to determine structural properties of a network, such as the distribution of vertex degrees and the diameter of the graph. A vast number of graph measures exist, and the production of useful ones for various domains remains an active area of research. Secondly, analysis to find a measurable quantity within the network, for example, for a transportation network, the level of vehicular flow within any portion of it.
Graph theory is also used to study molecules in chemistry and physics. In condensed matter physics, the three dimensional structure of complicated simulated atomic structures can be studied quantitatively by gathering statistics on graph-theoretic properties related to the topology of the atoms. For example, Franzblau's shortest-path (SP) rings. In chemistry a graph makes a natural model for a molecule, where vertices represent atoms and edges bonds. This approach is especially used in computer processing of molecular structures, ranging from chemical editors to database searching.
Graph theory is also widely used in sociology as a way, for example, to measure actors' prestige or to explore diffusion mechanisms, notably through the use of social network analysis software.
References
- Berge, Claude, Théorie des graphes et ses applications. Collection Universitaire de Mathématiques, II Dunod, Paris 1958, viii+277 pp. (English edition, Wiley 1961; Methuen & Co, New York 1962; Russian, Moscow 1961; Spanish, Mexico 1962; Roumanian, Bucharest 1969; Chinese, Shanghai 1963; Second printing of the 1962 first English edition. Dover, New York 2001)
-
id="CITEREFPelle1996">Pelle, Stéphane (1996), La Théorie des Graphes, Saint-Mandé: École Nationale des Sciences Géographiques, <[1]
- Chartrand, Gary, Introductory Graph Theory, Dover. ISBN 0-486-24775-9.
- Biggs, N.; Lloyd, E. & Wilson, R. Graph Theory, 1736-1936 Oxford University Press, 1986
- Harary, Frank, Graph Theory, Addison-Wesley, Reading, MA, 1969.
- Harary, Frank, and Palmer, Edgar M., Graphical Enumeration (1973), Academic Press, New York, NY.
See also
- Gallery of named graphs
- Glossary of graph theory
- List of graph theory topics
- Publications in graph theory
Related topics
Algorithms
Subareas
- Metric graph theory
- Probabilistic graph theory
- Topological graph theory
Related areas of mathematics
Prominent graph theorists
- Harary, Frank
- König, Denes
- Lovász, László
- Nešetřil, Jaroslav
- Rényi, Alfréd
- Robertson, Neil
Notes
1. ^ Biggs, N.; Lloyd, E. and Wilson, R. (1986). Graph Theory, 1736-1936. Oxford University Press.
2. ^ Cauchy, A.L. (1813). "Recherche sur les polyèdres - premier mémoire". Journal de l'Ecole Polytechnique 9 (Cahier 16): 66–86.
3. ^ L'Huillier, S.-A.-J. (1861). "Mémoire sur la polyèdrométrie". Annales de Mathématiques 3: 169–189.
4. ^ Cayley, A. (1875). "?". Berichte der deutschen Chemischen Gesellschaft 8: 1056–1059.
5. ^ Sylvester, J.J. (1878). "Chemistry and Algebra". Nature 17: 284.
6. ^ Appel, K. and Haken, W. (1977). "Every planar map is four colorable. Part I. Discharging". Illinois J. Math. 21: 429-490.
7. ^ Appel, K. and Haken, W. (1977). "Every planar map is four colorable. Part II. Reducibility". Illinois J. Math. 21: 491-567.
8. ^ Robertson, N.; Sanders, D.; Seymour, P. and Thomas, R. (1997). "The four color theorem". Journal of Combinatorial Theory Series B 70: 2-44.
External links
- More people and publications at: Graph Theory White Pages
- Online textbooks
- Graph Theory (1997/2005) by Reinhard Diestel
- Graph Theory with Applications (1976) by Bondy and Murty
- Encyclopaedia Britannica, Graph Theory
- Phase Transitions in Combinatorial Optimization Problems, Section 3: Introduction to Graphs (2006) by Hartmann and Weigt
- Chapters 1,2,4,5,7,10 and 12 of Digraphs: Theory Algorithms and Applications 2001 by Jorgen Bang-Jensen and Gregory Gutin
- Other resources
- Graph theory tutorial
- The compendium of algorithm visualisation sites
- Challenging Benchmarks for Maximum Clique, Maximum Independent Set, Minimum Vertex Cover and Vertex Coloring
- Image gallery: graphs
- Image gallery: example graphs
- Useful tools and Explanation
- Grafos Spanish copyleft software
- Graph Theory Resources
- GraphViz open source software to produce graph images from a description of the graph
- http://graphexploration.cond.org/ GUESS Graph Exploration System( Open Source GPL )
- Eric W. Weisstein, Graph Theory at MathWorld., hosted by the makers of Mathematicahttp://www.wolfram.com/
- DGLib -- a Directed Graph Library implementation - used in GRASS GIS
Mathematics (colloquially, maths or math) is the body of knowledge centered on such concepts as quantity, structure, space, and change, and also the academic discipline that studies them. Benjamin Peirce called it "the science that draws necessary conclusions".
..... Click the link for more information.Computer science, or computing science, is the study of the theoretical foundations of information and computation and their implementation and application in computer systems.
..... Click the link for more information.graph is the basic object of study in graph theory. Informally speaking, a graph is a set of objects called points, nodes, or vertices connected by links called lines or edges.
..... Click the link for more information.vertex (plural vertices) or node is the fundamental unit out of which graphs are formed: an undirected graph consists of a set of vertices and a set of edges (unordered pairs of vertices), while a directed graph consists of a set of vertices and a set of arcs (ordered
..... Click the link for more information.graph is the basic object of study in graph theory. Informally speaking, a graph is a set of objects called points, nodes, or vertices connected by links called lines or edges.
..... Click the link for more information.graph of a function f is the collection of all ordered pairs (x,f(x)). In particular, graph means the graphical representation of this collection, in the form of a curve or surface, together with axes, etc.
..... Click the link for more information.Graph may refer to:- A chart, a graphic representing tabular data or functions
- A graph used in visualising scientific data, representing the relationship between two or more variables
..... Click the link for more information.Leonhard Euler
Portrait by Johann Georg Brucker
Born March 15 1707
Basel, Switzerland
Died September 18 [O.S.
..... Click the link for more information.Seven Bridges of Königsberg is a famous solved mathematics problem inspired by an actual place and situation. The city of Königsberg, Prussia (now Kaliningrad, Russia) is set on the Pregel River, and included two large islands which were connected to each other and the mainland by
..... Click the link for more information.17th century - 18th century - 19th century
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1733 1734 1735 - 1736 - 1737 1738 1739
:
Subjects: Archaeology - Architecture -
..... Click the link for more information.Alexandre-Théophile Vandermonde (28 February 1735 – 1 January 1796) was a French musician and chemist who worked with Bezout and Lavoisier; his name is now principally associated with determinant theory in mathematics. He was born in Paris, and died there.
..... Click the link for more information.Knight's Tour is a mathematical problem involving a knight on a chessboard. The knight is placed on the empty board and, moving according to the rules of chess, must visit each square exactly once.
..... Click the link for more information.Gottfried Wilhelm Leibniz
Gottfried Wilhelm Leibniz
Born July 1 (June 21 Old Style) 1646
Leipzig, Electorate of Saxony
Died November 14 1716
Hannover, Hanover
Nationality German
..... Click the link for more information.Augustin Louis Cauchy
Augustin Louis Cauchy
Born 21 July 1789
Dijon, France
Died 23 May 1857 (aged 69)
..... Click the link for more information.Simon Antoine Jean L'Huillier (Geneva, 24 April 1750 - Geneva, 28 March 1840) was a Swiss mathematician of French Hugenot descent. He is known for his work in mathematical analysis and topology, and in particular the generalization of Euler's formula for planar graphs.
..... Click the link for more information.Topology (Greek topos, "place," and logos, "study") is a branch of mathematics that is an extension of geometry. Topology begins with a consideration of the nature of space, investigating both its fine structure and its global structure.
..... Click the link for more information.Калинингра? (Russian)
Kaliningrad on the map of the Baltic region in Europe
..... Click the link for more information.Johann Benedict Listing (July 25, 1808 – December 24 1882) was a German mathematician.
Listing was born in Frankfurt and died in Göttingen. In 1847, he wrote a famous article on topology, although he had introduced the term in correspondence some years earlier.
..... Click the link for more information.Arthur Cayley
Arthur Cayley
Born July 16 1821
Richmond, Surrey, UK
Died January 26 1895 (aged 75)
Cambridge, UK
..... Click the link for more information.Differential calculus, a field in mathematics, is the study of how functions change when their inputs change. The primary object of study in differential calculus is the derivative.
..... Click the link for more information.In graph theory, a tree is a graph in which any two vertices are connected by exactly one path. Alternatively, any connected graph with no cycles is a tree. A forest is a disjoint union of trees.
..... Click the link for more information.Editing of this page by unregistered or newly registered users is currently disabled due to vandalism.
If you are prevented from editing this page, and you wish to make a change, please discuss changes on the talk page, request unprotection, log in, or .
..... Click the link for more information.Graph enumeration is a subject of graph theory that deals with the problems of the following type: find how many non-isomorphic graphs have a given property.
See Pólya enumeration theorem for examples.
..... Click the link for more information.George Pólya (December 13, 1887 – September 7, 1985, in Hungarian Pólya György) was a Hungarian mathematician.Life and works
He was born as György Pólya in Budapest, Hungary, and died in Palo Alto, USA.
..... Click the link for more information.19th century - 20th century - 21st century
1900s 1910s 1920s - 1930s - 1940s 1950s 1960s
1932 1933 1934 - 1935 - 1936 1937 1938
Year 1935 (MCMXXXV
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1926 1927 1928 - 1929 - 1930 1931 1932
Year 1937 (MCMXXXVII
..... Click the link for more information.Nicolaas Govert de Bruijn (born 9 July, 1918) is a Dutch mathematician, affiliated as professor emeritus with the Eindhoven University of Technology.
De Bruijn covered many areas of mathematics. He is especially noted for the invention of the De Bruijn sequence.
..... Click the link for more information.20th century - 21st century
1920s 1930s 1940s - 1950s - 1960s 1970s 1980s
1956 1957 1958 - 1959 - 1960 1961 1962
Year 1959 (MCMLIX
..... Click the link for more information.James Joseph Sylvester (September 3, 1814 London – March 15, 1897 Oxford) was an English mathematician. He made fundamental contributions to matrix theory, invariant theory, number theory, partition theory and combinatorics.
..... Click the link for more information.18th century - 19th century - 20th century
1840s 1850s 1860s - 1870s - 1880s 1890s 1900s
1875 1876 1877 - 1878 - 1879 1880 1881
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Subjects: Archaeology - Architecture -
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