stilhere4huniid/Mall-of-Zimbabwe-Revenue-Optimizer

"A Data Science Digital Twin using Linear Programming (PuLP) and XGBoost to simulate tenant demand and optimize leasing revenue ($33M/yr) for the upcoming Mall of Zimbabwe (WestProp Holdings). # 🇿🇼 Mall of Zimbabwe: AI Revenue Optimization Engine ### 🚀 Project Overview This project is a **Strategic Digital Twin** designed to simulate the pre-construction leasing phase of the **Mall of Zimbabwe ($100M Project)**. Using **Machine Learning (XGBoost)** and **Linear Programming (PuLP)**, this engine solves the "Tenant Tetris" problem: How do we fill 90,000m² of space with the perfect mix of 150+ tenants to maximize revenue while ensuring financial stability? ### 📊 Key Results * **Projected Annual Revenue:** $33,686,562 (Optimized) * **Occupancy Rate:** 87.5% (Strategic Exclusivity) * **Top Revenue Driver:** Zone A (The Galleria) contributing $1.1M/month. * **Risk Mitigation:** AI filtered out 15% of applicants with high default probability. ### 🛠️ Tech Stack * **Language:** Python 3.9 * **Optimization:** `PuLP` (Linear Programming for Space Allocation) * **Machine Learning:** `XGBoost` (Tenant Credit/Viability Scoring) * **Data Processing:** `Pandas`, `NumPy` * **Visualization:** `Streamlit` (Interactive Dashboard), `Plotly` ### ⚡ Quick Start Want to run the **Revenue Optimization Dashboard** on your local machine? Follow these steps: **1. Clone the Repository** ```bash git clone github.com cd Mall-of-Zimbabwe-Revenue-Optimizer ``` **2. Install Dependencies** ```bash pip install -r requirements.txt ``` **3. Run the Dashboard** ```bash streamlit run dashboard/app.py > The Leasing Director Dashboard will open automatically in your browser at localhost ``` ### 🏗️ Project Structure * `data/`: Contains synthetic tenant applications and floorplan constraints. * `notebooks/`: Jupyter notebooks for Data Generation, ML Scoring, and Optimization. * `dashboard/`: Source code for the Streamlit Executive Dashboard. * `reports/`: PDF generation scripts for the "Confidential Strategy Brief". ### ⚠️ Disclaimer This is an independent Data Science Portfolio Project created for educational pur …