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There exist fixed-parameter tractable algorithms to solve the metric dimension problem for the parameters "vertex cover", [13] "max leaf number", [14] and "modular width". [9] Graphs with bounded cyclomatic number, vertex cover number or max leaf number all have bounded treewidth, however it is an open problem to determine the complexity of the ...
In mathematics and computer science, graph theory is the study of graphs, which are mathematical structures used to model pairwise relations between objects. A graph in this context is made up of vertices (also called nodes or points ) which are connected by edges (also called arcs , links or lines ).
A decision version of the problem (testing whether some vertex u occurs before some vertex v in this order) is P-complete, [12] meaning that it is "a nightmare for parallel processing". [13]: 189 A depth-first search ordering (not necessarily the lexicographic one), can be computed by a randomized parallel algorithm in the complexity class RNC ...
Computers and Intractability: A Guide to the Theory of NP-Completeness. Series of Books in the Mathematical Sciences (1st ed.). New York: W. H. Freeman and Company. ISBN 9780716710455. MR 0519066. OCLC 247570676.. This book is a classic, developing the theory, then cataloguing many NP-Complete problems. Cook, S.A. (1971). "The complexity of ...
Download as PDF; Printable version; In other projects Wikidata item; ... Pages in category "Unsolved problems in graph theory" The following 32 pages are in this ...
The problems of finding a Hamiltonian path and a Hamiltonian cycle can be related as follows: In one direction, the Hamiltonian path problem for graph G can be related to the Hamiltonian cycle problem in a graph H obtained from G by adding a new universal vertex x, connecting x to all vertices of G. Thus, finding a Hamiltonian path cannot be ...
Shortest path (A, C, E, D, F), blue, between vertices A and F in the weighted directed graph. In graph theory, the shortest path problem is the problem of finding a path between two vertices (or nodes) in a graph such that the sum of the weights of its constituent edges is minimized.
As of 2017 it can be solved in time O(1.1996 n) using polynomial space. [9] When restricted to graphs with maximum degree 3, it can be solved in time O(1.0836 n). [10] For many classes of graphs, a maximum weight independent set may be found in polynomial time. Famous examples are claw-free graphs, [11] P 5-free graphs [12] and perfect graphs. [13]