Weng Kee Wong: Nature-Inspired Metaheuristic Algorithms for Generating Optimal Experimental Designs

Particle swarm optimization (PSO) is a relatively new, simple and powerful way to search for an optimal solution.It is widely used in many applied fields.The method works quite magically and frequently finds the optimal solution or a nearly optimal solution after a few iterations.There is virtually no assumption required for the method to perform well and the user only needs to input a few easy to work with tuning parameters.

After a brief review of the theory of optimal design of experiments and recent advances in the field, I use several nonlinear models to demonstrate that PSO can find different kinds of optimal designs quickly, including mini-max types of optimal designs where effective algorithms to find such designs have remained elusive until now.