Python Script for Solving the Traveling Salesman Problem (TSP)

Description

• This script is designed to solve the Traveling Salesman Problem using the Branch and Bound method.
• It reads TSP data from text files, processes each file to find the minimum cost path, and writes the results to a CSV file.

Requirements

• Python 3.x
• NumPy library

Installation

Ensure that Python 3 is installed on your system. You can download it from https://www.python.org/downloads/

Install NumPy using pip:

pip install numpy

Usage

1. Place your TSP data files in a directory.
2. Open the script and modify the file path in the __main__ section to point to your directory containing the TSP data files.
3. Run the script using Python: python your_script_name.py (Here it is TSPusingbnb.py)

The script will process each file and write the results to 'tsp_results_bnb.csv' in the current directory.

Important Notes

• The script uses a Branch and Bound algorithm, which may take significant time for large datasets.
• I have mentioned #TODO in the script wherever changes are required.
• A timeout mechanism is implemented to stop processing a file if it takes too long, you can change the duration of this duration in the __main__. (I have taken 100 milliseconds)
• Change the value in the for loop in the __main__ section according to the number of data files you have.
• Modify the file_path variable in the __main__ section according to the location of your test data.
• The script creates a 'tsp_results_bnb.csv' file to store the results. Ensure you have write permissions in the directory where the script is run.