Algorithm to find the minimum spanning tree on a planar graph

In summary, the conversation is discussing different algorithms for finding the minimum spanning tree on a planar graph. The question is raised about the meaning of a planar graph having the property of the number of edges being in O(number of vertices). The answer key suggests that Kruskal's algorithm is the best option. The homework equations provide some analysis of the time complexities for each algorithm. It is concluded that this property means that there exists a constant that limits the number of edges in a planar graph based on the number of vertices.
  • #1
TheMathNoob
189
4

Homework Statement


I have the following algorithms: Prime MST with array, Prime MST with priorityq and Kruskal with priorityq. I have to choose the best algorithm to find the minimum spanning tree on a planar graph. A planar graph has the property in which the number of edges is in O(number of vertices). What does that mean?. The answer key says that kruskal is better.

Homework Equations


m=edges
n=vertices[/B]
Prime MST with array O(n^2+m)--> O(n^2)
Prime MST with pq: O(nlog(n)+mlog(n)) m>n O(mlogn)
Kruskal with pq: O(mlog(m))

The Attempt at a Solution


m in O(n) means to me that there is at most n number of edges and to me that looks weird because of the property of a maximal planar graph which says that at most a planar graph can have m= 3n-6 edges.
 
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  • #2
TheMathNoob said:
A planar graph has the property in which the number of edges is in O(number of vertices).
I would take that to mean that there exists some real constant C such that for every ##n\in\mathbb{N}##, the number of edges of every planar graph with ##n## vertices is less than or equal to ##Cn##. It is not necessarily the case that ##C=1## as you have surmised in your last paragraph.
 

Related to Algorithm to find the minimum spanning tree on a planar graph

1. What is a minimum spanning tree?

A minimum spanning tree is a subset of edges in a graph that connects all the vertices together without any cycles and with the minimum possible total edge weight.

2. Why is finding a minimum spanning tree important?

Finding a minimum spanning tree is important because it helps in finding the most efficient way to connect all the vertices in a graph, which can have various real-world applications such as designing transportation networks or communication networks.

3. How does the algorithm find the minimum spanning tree on a planar graph?

The algorithm starts by selecting an arbitrary vertex and adding it to the minimum spanning tree. Then, it repeatedly adds the edge with the minimum weight that connects the current tree to a new vertex. This process continues until all vertices are connected, resulting in a minimum spanning tree on the planar graph.

4. Can the algorithm find the minimum spanning tree on a graph with negative edge weights?

No, the algorithm cannot find the minimum spanning tree on a graph with negative edge weights. It is designed to only work on graphs with non-negative edge weights.

5. Are there any other algorithms for finding the minimum spanning tree on a planar graph?

Yes, there are other algorithms such as Kruskal's algorithm and Prim's algorithm that can also find the minimum spanning tree on a planar graph. However, the algorithm for finding the minimum spanning tree on a planar graph is specifically designed for graphs with non-negative edge weights.

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