FindMaximumCut
gives the maximum cut of the graph g.
Details and Options
- FindMaximumCut is also known as the max-cut problem.
- Typically used in cluster analysis, VLSI design and statistical physics.
- A maximum cut of a graph g is a partition of the vertices of g into two disjoint subsets with the largest number of edges between them.
- FindMaximumCut returns a list of the form {cmin,{c1,c2}}, where cmin is the value of a maximum cut found, and {c1,c2} is a partition of the vertices for which it is found.
- For weighted graphs, FindMaximumCut gives a partition {c1,c2} with the largest sum of edge weights possible between the sets ci.
- The following options can be given:
-
EdgeWeight Automatic edge weight for each edge PerformanceGoal "Speed" aspects of performance to try to optimize
Examples
open allclose allScope (5)
FindMaximumCut works with undirected graphs:
Options (1)
EdgeWeight (1)
By default, the edge weight of an edge is taken to be its EdgeWeight property if available, otherwise 1.
Use EdgeWeight->weights to set the edge weight:
Properties & Relations (1)
Use FindGraphPartition to find a cut with approximately equal-sized parts:
Text
Wolfram Research (2020), FindMaximumCut, Wolfram Language function, https://reference.wolfram.com/language/ref/FindMaximumCut.html.
CMS
Wolfram Language. 2020. "FindMaximumCut." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/ref/FindMaximumCut.html.
APA
Wolfram Language. (2020). FindMaximumCut. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/FindMaximumCut.html