Conclusion

After experiencing a strong surge in popularity in the 1990s and 2000s, the field of evolutionary algorithms remains remarkably active.

• At the theoretical level: significant work, mainly concerning the study of the convergence of these algorithms (Markov chain modeling), has laid solid foundations for these techniques, which were initially criticized for their "empirical" nature. These approaches provide a rich theoretical framework that allows for the refinement of many convergence and efficiency analyses.

• At the application level: the areas of application are very diverse, and these algorithms are widely used in research and industry.

  From an experimental point of view, these algorithms are effective for searching within difficult and irregular multidimensional spaces, limiting the risk of premature...