🔍 Operations Research – Max Flow with Ford-Fulkerson

Welcome to this Operations Research project dedicated to the implementation and visualization of the Ford-Fulkerson algorithm for finding the maximum flow in a directed graph.

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📦 Project Structure

RO/
├── RO-Service/          # Backend Flask (Ford-Fulkerson algorithm)
└── RO-Visualisation/    # Frontend React + Vite (visualization interface)

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📖 About

The goal is to provide an educational and interactive tool to:

• Simulate flow graphs (capacities, source, sink)
• Run the Ford-Fulkerson algorithm step by step
• Dynamically visualize augmenting paths, flows, and cuts

This project is particularly useful for courses in operations research, algorithms, or applied mathematics.

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⚙️ Installation

🔧 1. Backend – RO-Service (Flask)

📍 Folder: RO/RO-Service

🐍 Prerequisites

• Python 3.8+
• virtualenv or venv

🚀 Start the backend

cd RO-Service
python3 -m venv venv
source venv/bin/activate  # Windows : env\Scripts\activate
pip install flask flask-cors

# Start the server
python run.py

By default, the backend runs at: http://localhost:4321/api/

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🌐 2. Frontend – RO-Visualisation (React + Vite)

📍 Folder: RO/RO-Visualisation

📦 Prerequisites

• Node.js
• Yarn (recommended)

📁 .env file

Create a .env file at the root of RO-Visualisation:

VITE_API_BASE_URL=http://localhost:4321/api/

Replace the URL if your backend runs on another network/IP.

🚀 Install and launch

cd RO-Visualisation
yarn
yarn dev

By default, the frontend is accessible at: http://localhost:5173/

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🧠 About Ford-Fulkerson

The Ford-Fulkerson algorithm aims to maximize the flow between a source node and a sink node in a directed graph using augmenting paths.

The algorithm is based on the idea of traversing the graph to find paths with positive residual capacities, and increasing the flow along these paths until none can be found.

📜 License

This project is open-source under the MIT license.

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🚀 Author

@wharton-git