The term "cyclic graph" is not well-defined.
If you mean a graph that is not acyclic, then the answer is 3. That would be the union of a complete graph on 3 vertices and any number of isolated vertices.
If you mean a graph that is (isomorphic to) a cycle, then the answer is n.
If you are really asking the maximum number of edges, then that would be the triangle numbers such as n (n-1) /2.
n-1
V*(V-1)/2
No.No.No.No.
o(n^2)
Oh, dude, let me break it down for you. So, each vertex has degree 2, which means each vertex is connected to two edges. Since there are 7 vertices, you would have 7 * 2 = 14 edges in total. Easy peasy, right?
n-1
A minimum edge cover in graph theory is a set of edges that covers all the vertices in a graph with the fewest number of edges possible. It is significant because it helps identify the smallest number of edges needed to connect all the vertices in a graph. This impacts the overall structure of a graph by showing the essential connections between vertices and highlighting the relationships within the graph.
The vertex cover greedy algorithm helps in selecting the minimum number of vertices in a graph to cover all edges. It works by choosing vertices that cover the most uncovered edges at each step, leading to an efficient way to find a minimum vertex cover.
n-1 (o-o-o-o-o)
No, the complete graph of 5 vertices is non planar. because we cant make any such complete graph which draw without cross over the edges . if there exist any crossing with respect to edges then the graph is non planar.Note:- a graph which contain minimum one edge from one vertex to another is called as complete graph...
Yes.
If all the vertices and edges of a graph A are in graph B then graph A is a sub graph of B.
A drawing of a graph or network diagram is a pictorial representation of the vertices and edges of a graph. This drawing should not be confused with the graph itself: very different layouts can correspond to the same graph. In the abstract, all that matters is which pairs of vertices are connected by edges.
The vertex cover problem can be reduced to the set cover problem by representing each vertex in the graph as a set of edges incident to that vertex. This transformation allows us to find a minimum set of sets that cover all the edges in the graph, which is equivalent to finding a minimum set of vertices that cover all the edges in the graph.
11......
- Two or more edges that join the same pair of vertices in a graph. Also known as multiple edges.
The runtime complexity of Kruskal's algorithm is O(E log V), where E is the number of edges and V is the number of vertices in the graph.