📘 Pricing Optimization for Multi-Format Publishing

This project provides a mathematical and computational framework for optimizing the price structure of published works (ebooks, paperbacks, retail, etc.) across different distribution channels with varying royalty margins.

📊 Output

The script returns a ranked summary table showing:

• Optimal price for each platform
• Per-unit royalty (your earnings)
• A “support ranking” showing which format benefits you most

🧮 Mathematical Formulation

See problem.typ for the full write-up, including constraints, objective, and rationale.

🐍 Code Usage

Install required Python packages:

uv sync

You can run uv run <script_name.py> to execute the script depending on which one you want to run.

📄 Files Included

There are a few implementations that have similar results, our preferred is op_cvx.py as we found it to be the most efficient and accurate. Other ones are also optimizer.py and rules.py which implement the problem in different ways.

🧠 Concepts Involved

• Linear and nonlinear programming
• Royalties and margin modeling
• Consumer pricing psychology
• Optimization under inequality constraints

📬 License

MIT License — free for educational, nonprofit, and commercial use. Please cite or credit when used in publications.