Multi Objective Genetic Programming

Multi-objective genetic programming (MOGP) optimizes multiple, often conflicting, objectives simultaneously within the framework of genetic programming, aiming to discover solutions that effectively balance these competing goals. Current research focuses on applying MOGP to diverse problems, including designing neural network architectures for cognitive diagnosis, optimizing the geometry of physical systems like quadrupole magnets, and improving energy-efficient image compression algorithms. These applications highlight MOGP's ability to find superior solutions compared to single-objective approaches and its growing importance in various fields requiring efficient and interpretable models.