Math Problem Statement
Solution
The problem asks to apply the Nearest Neighbor Algorithm to find an approximate Minimum Hamiltonian Circuit for the given graph, starting at vertex A.
Steps to Apply the Nearest Neighbor Algorithm:
- Start at vertex A.
- At each step, move to the closest vertex (one with the smallest edge weight that has not been visited yet).
- Repeat the process until all vertices are visited.
- Return to the starting vertex A to complete the circuit.
Applying the Nearest Neighbor Algorithm:
-
Start at A:
- From A, the closest neighbor is C (edge weight = 1).
- Path: A → C
-
At C:
- From C, the closest unvisited neighbor is B (edge weight = 2).
- Path: A → C → B
-
At B:
- From B, the closest unvisited neighbor is D (edge weight = 6).
- Path: A → C → B → D
-
At D:
- From D, the closest unvisited neighbor is E (edge weight = 4).
- Path: A → C → B → D → E
-
At E:
- The only unvisited vertex left is F (edge weight = 8).
- Path: A → C → B → D → E → F
-
At F:
- Now return to A (edge weight = 7).
- Path: A → C → B → D → E → F → A
Final Approximate Minimum Hamiltonian Circuit:
The path following the Nearest Neighbor Algorithm is:
Total weight of the path:
1 (A to C) + 2 (C to B) + 6 (B to D) + 4 (D to E) + 8 (E to F) + 7 (F to A) = 28.
Let me know if you need more details or clarifications!
Related Questions:
- How does the Nearest Neighbor Algorithm compare to other algorithms for the Traveling Salesman Problem?
- Can the Nearest Neighbor Algorithm guarantee the optimal Hamiltonian circuit?
- What are some limitations of the Nearest Neighbor Algorithm?
- How would the solution change if starting from a different vertex?
- What is the significance of edge weights in the context of real-world applications?
Tip:
When using the Nearest Neighbor Algorithm, the order of visiting vertices can vary significantly depending on the starting point, potentially leading to different solutions with varying total weights.
Ask a new question for Free
By Image
Drop file here or Click Here to upload
Math Problem Analysis
Mathematical Concepts
Graph Theory
Traveling Salesman Problem (TSP)
Nearest Neighbor Algorithm
Hamiltonian Circuit
Formulas
Minimum Hamiltonian Circuit Approximation using Nearest Neighbor Algorithm
Theorems
Hamiltonian Circuit Theorem
Graph Optimization
Suitable Grade Level
Undergraduate level, or advanced high school (Grades 11-12)
Related Recommendation
Nearest Neighbor Algorithm Applied to Hamiltonian Circuit Starting at Vertex A
Nearest Neighbor Algorithm: Graph Path Starting at Vertex A
Nearest Neighbor Algorithm Solution for a Weighted Graph Starting at Vertex A
Nearest Neighbor Algorithm: Graph Pathfinding from Vertex A
Estimating the Cheapest Hamiltonian Circuit using Nearest Neighbor Method