Dietary Optimization Project

Overview

This project aims to optimize dietary patterns for the average Iranian individual using linear programming techniques. The focus is on achieving a balance between nutritional adequacy, affordability, cultural acceptance, and sustainability. This project integrates research-backed methodologies and mathematical modeling to address dietary and economic challenges.

Features

• Mathematical Modeling: Utilizes linear programming to create optimal meal plans while adhering to daily nutritional requirements and budget constraints.
• Customizable Parameters: Adjustable dietary constraints and user preferences for flexible meal planning.
• Data Analysis: Analyzes nutritional values and cost efficiency to generate practical dietary recommendations.
• Visualization: Generates insightful plots for nutritional values and daily meal costs to support decision-making.

Repository Structure

• src/: Contains the Python scripts, including the main optimization script (Final_code.py).
• data/: Holds datasets like nutritional information and cost data for meals.
• docs/: Includes detailed documentation and the final research paper (Final-word.docx).
• outputs/: Stores generated visual outputs such as meals planned for each day.png .

How to Run

1. Dependencies: Install required Python libraries listed in requirements.txt.

   pip install -r requirements.txt

2. Data Preparation: Place the dataset (e.g., OR_project - Sheet1 (2).csv) in the data/ folder.

3. Run the Code:

   python src/Final_code.py

4. View Outputs:

   • Generated meal plans and summaries will be printed to the console.
   • Visualization plots (nutritional values and costs) will be saved in the outputs/ directory.

Goals

• To design an affordable, nutritionally adequate meal plan for the average Iranian individual.
• To ensure cultural relevance and sustainability in dietary recommendations.
• To provide a scalable solution for policy-makers and individuals in similar socio-economic contexts.

Research Insights

This project is supported by an extensive review of dietary optimization techniques and their applications. The research paper (Final-word.docx) provides detailed insights into the methodology, data sources, and results achieved through this project.

Key Findings

• Caloric Efficiency: Optimization reduced caloric intake to align with health recommendations while minimizing waste.
• Protein Adequacy: Improved protein intake compared to historical averages.
• Cost Reduction: Demonstrated significant cost savings while maintaining nutritional adequacy.

Future Work

• Expanding the dataset to include broader dietary preferences and regional variations.
• Enhancing user interactivity for custom dietary constraints and goals.
• Incorporating environmental sustainability metrics into the optimization model.

Acknowledgments

This project was developed by:

• Pouriya Khodaparast
  pooriyakh@aut.ac.ir
• Kimia Rasoulikeshvar
  kimia.rasoulikeshvar@aut.ac.ir
• Seyed Emad Hosseini
  emad.hosseini@aut.ac.ir
• Navid mombeni(adviser) mombeninavid@gmail.com

For further details, refer to the research paper in the docs/ directory.