# 🧮 Combinatorial Optimization

This repository contains Python implementations of classic **combinatorial optimization algorithms**, tackling problems where the goal is to find the best solution from a finite set of possible solutions.

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## 🧠 Covered Algorithms

- **Travelling Salesman Problem (TSP)** – Brute-force, Greedy, Dynamic Programming
- **0/1 Knapsack Problem** – Recursive, Memoization, Tabulation (DP)
- **Graph Problems** – Shortest paths, MST (Kruskal, Prim)
- **Scheduling** – Greedy job selection
- **Set Cover, Subset Sum**, etc.

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## 📂 Project Structure

Combinatorial-Optimization/ ├── tsp/ │ └── tsp_greedy.py │ └── tsp_dp.py ├── knapsack/ │ └── knapsack_recursive.py │ └── knapsack_dp.py ├── graphs/ │ └── prims.py │ └── kruskal.py ├── utils/ │ └── data_loader.py ├── README.md

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## 🧪 How to Run

```bash
# Example: Run the TSP greedy solution
python tsp/tsp_greedy.py

Each file contains a main() function for demonstration and testing.

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📌 Sample: TSP Output

Visited path: A → D → B → C → A
Total distance: 142

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🎯 Applications

• Logistics & routing
• Scheduling tasks
• Resource allocation
• Game AI
• Network design

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👨‍💻 Author

Do Nguyen Anh Tuan 🎓 MSc in Information Technology @ Lac Hong University 🏢 FabLab @ EIU | Passionate about optimization, AI & ML 🌐 Portfolio Website