Diet Planner Evolutionary Algorithm

This project uses an evolutionary algorithm (NSGA-II) to solve a diet planning problem. The goal is to find the optimal diet plan that meets certain nutritional requirements while maximizing variety.

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

Prerequisites

You need Python 3.x and the following libraries installed on your machine:

• numpy
• matplotlib
• jmetalpy

You can install these packages using pip:

pip install numpy matplotlib jmetalpy

Running the Program

To run the program, navigate to the project directory and run the main.py script with the instance number and project name as arguments:

python main.py 1 my_project

In this example, 1 is the instance number and my_project is the project name.

The program will create a new directory in the output folder with the name of your project. Inside this directory, it will generate a .csv file with the results of the algorithm and a .txt file with detailed information about each execution. It will also generate a scatter plot of the Pareto optimal solutions.

Executed Instances for Research

The following instances were executed for the research:

• Instance 1: python main.py 1 instance_1

• Instance 2: python main.py 2 instance_2

Project Structure

• main.py: This is the main script that you run to start the program.
• src/models: This directory contains the classes used in the program, including Args, Config, CrossoverCustom, DietProblem, and Result.
• src/utils: This directory contains utility functions.
• config: This directory contains configuration files for the algorithm and the diet problem model.
• data: This directory contains the food data in a .csv file.
• output: This directory is where the program saves the results.

Authors

• Jorge Miguel Machado
• Santiago Pereira