Programming project from the course INF421: Design and Analysis of Algorithms at École Polytechnique. The problem statement is provided.
In this project we consider the pseudo-boolean optimization problem. Let
Our goal is to compute
The project was implemented using the Python programming language. A requirements.txt file with all project dependencies is provided.
All the code can be found in the code folder in the repository.
cd code
Now, to generate the scatter plots for the empiric runtime analysis of the OneMax and LeadingOnes benchmark functions (as described in task 2) we run the EmpiricRunTimes.py file. The generated plots are saved in the plots folder.
python EmpiricRunTimes.py
To generate a series of plots for the empirical diversity tests of the Jumpk benchmark function using the
python GAtests.py
Unit tests are also provided in the unit_tests folder.
For further reading: Andrew N. Sloss and Steven Gustafson; 2019 Evolutionary Algorithms Review