Math Problem Statement

Answers

Using Prim's and Kruskal's algorithms to find the Minimum Spanning Tree (MST) of a weighted graph.

Solution

Let’s solve the questions step-by-step based on the given weighted graph and instructions:

4. Using Prim's algorithm (starting at vertex ee):

Prim's algorithm starts at a specific vertex (here, ee) and grows the minimum spanning tree (MST) by adding the smallest-weight edge connecting the tree to a vertex not yet in the tree.

Steps:

  1. Start at vertex ee. The edges connected to ee are:

    • efe \to f (weight = 5)
    • ege \to g (weight = 6)
    • ehe \to h (weight = 7)
    • ede \to d (weight = 8)
  2. Select the smallest edge: efe \to f (weight = 5). Add ff to the MST.

  3. Add the smallest edge connecting ff or ee to a new vertex:

    • fgf \to g (weight = 4)
    • fhf \to h (weight = 6)
    • fif \to i (weight = 4)
    • ege \to g (weight = 6)
    • ehe \to h (weight = 7)
    • ede \to d (weight = 8)

    Select fgf \to g (weight = 4). Add gg to the MST.

  4. Repeat for the remaining vertices, adding the smallest edge without forming a cycle:

    • Add fif \to i (weight = 4).
    • Add fhf \to h (weight = 6).
    • Add ede \to d (weight = 8).

MST Edges:

{(e,f),(f,g),(f,i),(f,h),(e,d)}\{(e, f), (f, g), (f, i), (f, h), (e, d)\}


5. Using Kruskal's algorithm:

Kruskal's algorithm sorts all edges by weight and selects edges in ascending order, avoiding cycles, until the MST is formed.

Steps:

  1. Sort edges:

    • fgf \to g (4)
    • fif \to i (4)
    • aba \to b (3)
    • ada \to d (3)
    • efe \to f (5)
    • fhf \to h (6)
    • ege \to g (6)
    • ehe \to h (7)
    • ede \to d (8)
  2. Select edges in ascending order:

    • fgf \to g (4)
    • fif \to i (4)
    • aba \to b (3)
    • ada \to d (3)
    • efe \to f (5)
    • fhf \to h (6)

MST Edges:

{(a,b),(a,d),(e,f),(f,g),(f,h),(f,i)}\{(a, b), (a, d), (e, f), (f, g), (f, h), (f, i)\}


6. Total weight of MST:

The sum of weights for the edges in the MST: 4+4+3+3+5+6=254 + 4 + 3 + 3 + 5 + 6 = 25


7. Using Prim's algorithm (starting at dd):

Follow the same process as in Question 4 but start at dd.

Steps:

  1. Start at dd. The edges connected to dd are:

    • dad \to a (weight = 3)
    • ded \to e (weight = 8)

    Select dad \to a (weight = 3). Add aa to the MST.

  2. Add the smallest edge:

    • aba \to b (weight = 3)
    • aea \to e (weight = 6)

    Select aba \to b (weight = 3).

  3. Continue until all vertices are included.

MST Edges:

Similar edges will result, since the MST structure is the same regardless of the starting vertex.

{(a,b),(a,d),(e,f),(f,g),(f,h),(f,i)}\{(a, b), (a, d), (e, f), (f, g), (f, h), (f, i)\}


Do you want detailed explanations of any step? Here are five questions you might explore further:

  1. How do Prim's and Kruskal's algorithms differ in approach and use cases?
  2. What happens if a different starting vertex is chosen for Prim's algorithm?
  3. Could there be multiple MSTs for the same graph? Why or why not?
  4. How would the algorithm handle negative edge weights in the graph?
  5. What is the computational complexity of Prim’s and Kruskal’s algorithms?

Tip: Always visualize the graph when applying MST algorithms to understand the tree's growth!

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Math Problem Analysis

Mathematical Concepts

Graph Theory
Minimum Spanning Tree
Prim's Algorithm
Kruskal's Algorithm

Formulas

Sorting edges by weight (Kruskal's)
Selecting the smallest weight edge to expand the MST (Prim's)

Theorems

Greedy Algorithm for MST
Correctness of Prim's Algorithm
Correctness of Kruskal's Algorithm

Suitable Grade Level

Undergraduate or Advanced High School