Dynamic Parameter Adaptation for Meta-Heuristic Optimization Algorithms Through Type-2 Fuzzy Logic

Proposes a methodology for parameter adaptation in meta-heuristic optimization methods
Uses three different optimization methods: PSO (Particle Swarm Optimization), ACO (Ant Colony Optimization) and GSA (Gravitational Search Algorithm), to verify the improvement of the proposed methodology
Demonstrates the advantage of the methodology by using various simulations

Contenu
Introduction.- Theory and Background.- Problems Statement.- Methodology.- Simulation Results.- Statistical Analysis and Comparison of Results.