Genetic Algorithm for 2D Guillotine Cutting Optimization

This program uses a genetic algorithm to find an optimal layout for a set of rectangular items on a 2D sheet. It loads item data from a CSV file, runs a genetic algorithm to find the best layout, and then visualizes the layout using a plot.

Requirements

• Python 3.x
• Matplotlib

Installation

To install the required libraries, you can use the following command:

pip install matplotlib

Usage

To run the program, you will need to provide the path to the CSV file containing the item data. You can do this by running the following command:

python main.py items.csv

This will load the item data from the CSV file, run the genetic algorithm, and then visualize the best layout.

Example CSV File

id,width,height
item1,10,5
item2,12,3
item3,8,7

Output

The program will print the best individual and its fitness (total area needed) to the console. It will also create a plot of the best layout.

References

• Toshihiko Ono's paper "Optimizing Two-dimensional Guillotine Cut by Genetic Algorithms" http://ono-t.d.dooo.jp/GA/GA-papers/TO-110.pdf