ludenyo/Routing-for-a-centralized-warehouse

Optimizing logistics in Kenya using K-Means clustering, Google OR-Tools for VRP, and GIS analysis. Improves route efficiency, and last-mile delivery while reducing costs and supporting sustainable, data-driven logistics in resource-constrained settings. ## 🗺️ Project Overview Routing for a Centralized Warehouse is a Django-based web application designed to simulate and analyze delivery routes from a centralized warehouse to multiple retail locations. The tool leverages K-Means clustering, Google OR-Tools for solving Vehicle Routing Problems (VRP), and GIS-based analysis to optimize logistics workflows in Kenya. It helps improve: - Warehouse placement decisions - Route efficiency for delivery vehicles - Last-mile delivery performance By reducing costs and improving delivery planning, the system promotes sustainable, data-driven logistics—especially valuable in resource-constrained environments. ## 🚀 Live Demo 🌐 View Live Application --- **Key Features:** - Interactive delivery route visualizations - Route optimization using Google OR-Tools - Vehicle allocation based on capacity constraints - Data import from Excel and CSV - Frontend rendered with Django templates --- ## ⚙️ Technologies Used - 🐍 Python 3 - 🌐 Django - 📊 Google OR-Tools - 📚 Pandas, NumPy, scikit-learn - 📄 openpyxl (for Excel file support) - 🔧 Render (for deployment) --- ## 🧰 Setup Instructions (Local Development) > Make sure you have Python 3 installed. 1. **Clone the repository:** git clone github.com cd Routing-for-a-centralized-warehouse 3. **Create and activate a virtual environment:** python3 -m venv venv source venv/bin/activate 4. Install dependencies: pip install -r requirements.txt 6. Run migrations: python manage.py migrate 8. Run the server: python manage.py runserver 9. Access the app: Open 127.0.0.1 in your browser. --- The application includes a simulation interface at the /SIMULATE route, which allows users to: - Simulate future delivery orders using sample shop and product data. - Visualize optimized delivery routes based on K-Means clustering and Vehicle Routing Problem (VRP) solutions. - Test logistics performance under hypothetical demand scenario …