MTH109 Pepperdine University Traveling Salesman Problem Paper Traveling Salesman Problem For this Critical Thinking assignment, you will solve a real-worl
MTH109 Pepperdine University Traveling Salesman Problem Paper Traveling Salesman Problem
For this Critical Thinking assignment, you will solve a real-world optimization problem using graph theory.
Part I: Complete the following steps:
Select a real-world optimization problem that is an example of the Traveling Salesman Problem (TSP).
Create a graph modeling the real-world scenario corresponding to the problem. Use weights to represent the variable that you are optimizing.
Find an optimal solution for the problem using the concepts studied in this module.
Part II: Based on your work in Part I, discuss the following:
Discuss your rationale for your choice of the real-world optimization problem. How were you able to identify that it was an example of the TSP? Why is this example relevant?
Describe how you created the graph modeling the real-world scenario corresponding to the problem.
Determine if the graph is complete. If so, use your graph to describe the formula for computing the number of Hamilton circuits.
Explain in detail how you solved the problem.
Describe a method for finding a non-optimal solution to the problem.
Consider another variable that could be optimized in the problem. How would your answers to Part I be affected by this change?
Discuss the advantages of using graph theory to solve this problem.
Requirements:
You must submit TWO files for this assignment. The first file should contain the computations, graphs, diagrams, etc., associated with the questions in Part I. This file may be formatted as a numbered list of answers. Unless stated in the problem, a narrative discussion is not required, but you must provide enough information to show how you arrived at the answer.
The second file should be a 2-3-page narrative paper, written in APA format, associated with the situation described in Part II. Specific requirements for the paper are provided below:
