🏬 Retail Inventory Optimization

A linear programming–based simulation project for optimizing product mix decisions in a retail store. This analysis balances profit contribution, cost, and shelf space to recommend the most profitable inventory allocation strategy.

📎 Download Full Report

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🎯 Project Highlights

• Objective: Maximize total profit while considering space and budget constraints
• Approach: Linear programming model formulated and solved using R
• Constraints:
  • Product shelf space availability
  • Budget limit
  • Minimum/maximum product quantities
• Key Takeaways:
  • Product 1 and 3 yield highest profit-to-space ratios
  • Increasing budget doesn't always lead to higher marginal profit
  • Sensitivity analysis reveals tight constraints with major impact

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🛠 Technologies Used

• Language: R
• Libraries: lpSolve, ggplot2, dplyr
• Modeling: Linear programming
• Visualization: Bar charts, scenario comparison plots

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📁 Files

• /code/ – R source code and optimization script
• /assets/ – Visualizations and charts
• /report/ – Final PDF report
• README.md – You are here

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📊 Visual Summary

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👨‍💻 About Me

I'm currently pursuing a Master’s in Analytics, focusing on real-world applications of optimization, modeling, and business intelligence. My academic projects blend decision science, R programming, and data storytelling.

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📬 Contact

Feel free to connect via LinkedIn
Or reach out via email: allen.lei.zhao@gmail.com
Portfolio: allenleizhao.github.io