What are the limitations of MST (Minimum Spanning Tree)?

What are the limitations of MST algorithms?

MST algorithms, like Prim's and Kruskal's, have limitations such as not handling negative weight edges and being inefficient for dense graphs.

Can MST algorithms be used for graphs with cycles?

Yes, MST algorithms can handle graphs with cycles, but they will only include the edges that contribute to the minimum spanning tree.

What happens if there are multiple MSTs for a graph?

If there are multiple MSTs, any of them can be considered valid as they all have the same total weight.

Are there any real-world applications where MST is not suitable?

Yes, MST is not suitable for scenarios requiring shortest paths or when edge weights can change dynamically.

How do MST algorithms perform with large datasets?

MST algorithms can struggle with large datasets, especially if the graph is dense, leading to higher computational costs.