Route Optimization Tool for Bangalore Locations

Overview

This project implements a route optimization solution using Python, specifically designed to find the most efficient path between multiple locations in Bangalore. It solves the Traveling Salesman Problem (TSP) using Google OR-Tools and provides an interactive visualization using Folium maps.

Features

• Optimizes delivery routes between multiple locations
• Calculates accurate geodesic distances between points
• Generates interactive map visualization
• Provides detailed route information in a table format
• Shows cumulative distance calculations
• Exports results to a single HTML file with side-by-side view

Prerequisites

• Python 3.8 or higher
• Required Python packages (see requirements.txt)

Installation

1. Clone the repository:

git clone https://github.com/shelwyn/route-optimization.git

cd route-optimization-bangalore

2. Create and activate a virtual environment (recommended):

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install required packages:

pip install -r requirements.txt

Usage

1. Update the locations in the code:

outlets = [
    (13.0378748,77.6017724),  # Hebbal
    (13.0215944,77.5508614),  # Yeshwantpur
    (12.9781839,77.6398741),  # Indiranagar
    (12.8583418,77.7808364),  # Sarjapura
    (13.0075813,77.6919984)   # KR Puram
]
outlet_names = ["Hebbal", "Yeshwantpur", "Indiranagar", "Sarjapura", "KR Puram"]

2. Run the script:

python app.py

3. Open the generated HTML file:

optimized_route_map.html

Output

The script generates an HTML file containing:

• Interactive map with numbered markers and route visualization
• Table showing route details including:
  • Starting and ending points for each segment
  • Distance between consecutive points
  • Cumulative distance traveled

Project Structure

route-optimization/
│
├── app.py                    # Main application file
├── requirements.txt          # Python dependencies
├── README.md                # Project documentation
└── optimized_route_map.html  # Generated output (after running script)

How It Works

1. Distance Calculation: Uses GeoPy to calculate accurate geodesic distances between locations
2. Route Optimization: Implements TSP solution using Google OR-Tools
3. Visualization: Creates interactive map using Folium and generates an HTML table
4. Output Generation: Combines map and table into a single HTML file with side-by-side layout

Customization

• Modify the outlets list to include different locations
• Adjust the map styling in the plot_route_on_map function
• Customize the table appearance in the CSS section of create_complete_html

Contributing

Feel free to fork this repository and submit pull requests. For major changes, please open an issue first to discuss what you would like to change.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• Google OR-Tools for the optimization engine
• Folium for map visualization
• GeoPy for distance calculations

Contact

For any queries or suggestions, please reach out to [Your Name/Email]