Multi-objective Optimization in Highly Complex Environments

Real optimization problems often combine several conflicting objectives with noisy measurements and uncertain parameters. This project develops techniques for multi-objective optimization in highly complex environments. It builds on work in uncertainty handling, archiving strategies, and automatic algorithm configuration. PAPIIT IA102923, UNAM, funds the project.