soldiermedic / assignment-2

Intro to AI: Assignment #2

Genetic Algorithm

Assignment-2

Intro to AI: Assignment #2

Traveling Salesperson Problem with Genetic Algorithm

This project solves the Traveling Salesperson Problem (TSP) using a Genetic Algorithm. The goal of the TSP is to find the shortest route that a salesperson can take to visit a given set of cities and return to the starting city.

Setup and Usage

1. Install the required dependencies by running pip install -r requirements.txt.

2. Select python interpretor we used: python 3.11

3. Run the Flask web application by running the sample-code.ipynb file by using jupyter notebook:

4. Open your web browser and access the application at http://localhost:5678.

5. The homepage provides an overview of the Traveling Salesperson Algorithm, explaining how it works and its applications.

6. Click on the "See our Genetic Algorithm Results" button to view the results of the Genetic Algorithm applied to the TSP.

7. The Genetic Algorithm implementation utilizes the genetic_algorithm.html template file and generates a plot of the best route using matplotlib.

• sample-code.ipynb: Contains the Flask application code.
• templates: Directory containing the HTML templates used by Flask.
• templates/index.html: The main page template displaying information about the Traveling Salesperson Algorithm.
• templates/genetic_algorithm.html: The template for displaying the results of the Genetic Algorithm.
• static: Directory to store static files such as images.
• static/plot.png: The plot image generated by the Genetic Algorithm.
• requirements.txt: File specifying the project's dependencies.
• README.md: This file providing an overview of the project.