🧠 Optimization Project with Gurobi & Streamlit

This project provides interactive solutions to two classic operations research problems using Gurobi Optimizer and a Streamlit interface:

• 🗺️ Facility Location Problem (FLP)
• 🏭 Factory Planning Problem (FPP)

Both models are fully parameterized and user-friendly, allowing you to input data and instantly get optimized results with visual feedback.

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🚀 Features

🗺️ Facility Location Problem

• Determine optimal locations for facilities to minimize total costs.
• Customize:
  • Number and location of facilities/customers.
  • Setup costs and per-mile transport costs.
• Solve and visualize:
  • Which facilities to build.
  • Shipment plan from facilities to customers.
  • Graphical plot of customer-facility relationships.

🏭 Factory Planning Problem

• Maximize total profit over several months by planning:
  • Production
  • Storage
  • Sales
• Configure:
  • Profits, storage cost, demand, and labor availability.
  • Raw material limits and usage.
  • Labor downtime periods.
• Output:
  • Optimal production and inventory plan.
  • Resource and raw material usage breakdown.

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📦 Tech Stack

• Gurobi Optimizer – High-performance solver for LP/MIP models.
• Streamlit – Intuitive and fast UI for model interaction.
• Matplotlib – Visualizing results for FLP.
• Pandas – Tabular data display and processing.

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📂 Project Structure

📁 optimization-project/
├── facility_location.py       # FLP model and visualization
├── factory_planning.py        # FPP model with Gurobi
├── Home.py                     # Streamlit interface
├── data/                      # (Optional) Data samples or templates
├── requirements.txt           # Dependencies
└── README.md                  # This file
 

🚀 How to Run

1. Clone the repository:

   git clone https://github.com/your-username/your-repo-name.git
   cd your-repo-name

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

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

3. Install dependencies:

   pip install -r requirements.txt

4. Run the Streamlit app:

   streamlit run Home.py