Use linear programming to create an optimal recipe for a cheap meal bar that meets specific nutritional requirements

Click on the image below to access a short explainer video to understand the concept behind this solution

As an R&D manager of a large food manufacturer, you need to design a recipe for a new cheap and healthy meal bar. Meal bars must function as a meal rather than just a snack to fill in the cracks.

7 ingredients are available Meat: Chicken, Beef, Mutton Non-Meat: Rice, Corn, Wheat bran, Peanuts

These ingredients have different nutrition facts (in grams) per gram

They also have different costs ($/gram)

Minimise the total cost per bar (Weight: 120g).

In this repository, you will find all the code used to explain the concepts presented in the article.

• Raw Materials Optimization.ipynb - Jupyter notebook with step-by-step analysis
• raw_materials_optimization.py - Standalone Python script

pip install -r requirements.txt
python raw_materials_optimization.py

• pandas
• pulp
• openpyxl

• The full write-up, with the reasoning behind the code: Raw Materials Optimization for Food Manufacturing with Python
• The video: Understand Raw Material Cost Optimisation in Food Manufacturing
• Test what you learned: the Supply Science App has the business optimisation quizzes, free and in the browser.
• 100+ case studies with their source code: samirsaci.com

Samir Saci, supply chain engineer and data scientist with ten years in operations across Asia and Europe. Founder of LogiGreen, creator of Supply Science. For consulting on analytics and sustainable supply chain transformation: LogiGreen. More about me: samirsaci.com/about · LinkedIn