Примеры использования Graph coloring на Английском языке и их переводы на Русский язык
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Tree-depth may also be defined using a form of graph coloring.
Graph coloring enjoys many practical applications as well as theoretical challenges.
Much research about triangle-free graphs has focused on graph coloring.
Chaitin is also the originator of using graph coloring to do register allocation in compiling, a process known as Chaitin's algorithm.
Pseudoforests also play a key role in parallel algorithms for graph coloring and related problems.
Many notions of graph coloring fit into this pattern and can be expressed as graph homomorphisms into different families of graphs. .
The Erdős-Faber-Lovász conjecture is another unproven statement relating graph coloring to cliques.
A linear coloring of a graph is a proper graph coloring in which the induced subgraph formed by each two colors is a linear forest.
These findings demonstrated the difficulty of efficiently computing approximate solutions to a number of minimization problems such as Graph coloring and Set covering.
In graph theory, the Erdős-Faber-Lovász conjecture is an unsolved problem about graph coloring, named after Paul Erdős, Vance Faber, and László Lovász, who formulated it in 1972.
Constructions of graphs with large values of chromatic number and girth, not just odd girth, are also possible, butmore complicated see Girth and graph coloring.
In a traditional graph coloring, each vertex in a graph is assigned some color, and adjacent vertices- those connected by edges- must be assigned different colors.
Some other optimization problems that are NP-complete onmore general graph families, including graph coloring, are similarly straightforward on split graphs.
There is a natural geometric perspective on graph colorings by observing that,as an assignment of natural numbers to each vertex, a graph coloring is a vector in the integer lattice.
In graph theory, the Heawood conjecture orRingel-Youngs theorem gives a lower bound for the number of colors that are necessary for graph coloring on a surface of a given genus.
Combinatorial analogs of concepts and methods in topology are used to study graph coloring, fair division, partitions, partially ordered sets, decision trees, necklace problems and discrete Morse theory.
It is named after Solomon W. Golomb, who constructed it(with a non-planar embedding)as a unit distance graph that requires four colors in any graph coloring.
For the perfect graphs, a number of NP-complete optimization problems(graph coloring problem, maximum clique problem, and maximum independent set problem) are polynomially solvable.
The Hadwiger conjecture states that the Hadwiger number is always at least as large as the chromatic number of G. That is, every graph with Hadwiger number k should have a graph coloring with at most k colors.
He used this approach not only for 3-coloring butas part of a more general graph coloring algorithm, and similar approaches to graph coloring have been refined by other authors since.
Apex-minor-free graph families obey a strengthened version of the graph structure theorem,leading to additional approximation algorithms for graph coloring and the travelling salesman problem.
Another example is the coalescing performed in global graph coloring register allocation, where vertices are contracted(where it is safe) in order to eliminate move operations between distinct variables.
Note that any coloring of a graph with the minimum number of colors must be a complete coloring, so minimizing the number of colors in a complete coloring is just a restatement of the standard graph coloring problem.
It is a unit distance graph requiring four colors in any graph coloring, and its existence can be used to prove that the chromatic number of the plane is at least four.
Because comparability graphs are perfect, many problems that are hard on moregeneral classes of graphs, including graph coloring and the independent set problem, can be computed in polynomial time for comparability graphs. .
In all perfect graphs, the graph coloring problem, maximum clique problem, and maximum independent set problem can all be solved in polynomial time Grötschel, Lovász& Schrijver 1988.
Once the vertices have been sorted by the numerical values that describe an indifference graph(or by the sequence of unit intervals in an interval representation) the same ordering can be used to find an optimal graph coloring for these graphs, to solve the shortest path problem, and to construct Hamiltonian paths and maximum matchings, all in linear time.
Since circle graph coloring with four or more colors is NP-hard, and since any circlegraph can be formed in this way from some book embedding problem, it follows that optimal book embedding is also NP-hard.
The set of nodes that are active simultaneously must be an independent set in graph G. An optimal fractional graph coloring in G then provides a shortest possible schedule, such that each node is active for(at least) 1 time unit in total, and at any point in time the set of active nodes is an independent set.