NEW ADVANCES IN ALGORITHMIC TECHNIQUES FOR THE COMPUTATION OF OPTIMAL DESIGNS
One of the biggest challenges in calculating optimal experimental designs is to cope with the computational cost. Algorithmic techniques remain key in this field: while analytical solutions are often impractical, numerical techniques have become the most effective option. This research provides an innovative algorithm that combines the algorithms traditionally used in Optimal experimental design with metaheuristic techniques. For this purpose we have suitably adapted the foundations of Wynn-Federov, multiplicative and the Particle Swarm Optimization algorithms. This combination not only enhances computational efficiency but also is more robust facing complex optimization problems.
Keywords: D-optimum design Multiplicative algorithm Wynn–Fedorov algorithm Particle Swarm Optimization Combined algorithm