Uncovering interactions in Plackett-Burman screening designs applied to analytical systems. A Monte Carlo ant colony optimization approach.

Abstract

Screening of relevant factors using Plackett-Burman designs is usual in analytical chemistry. It relies on the assumption that factor interactions are negligible; however, failure of recognizing such interactions may lead to incorrect results. Factor associations can be revealed by feature selection techniques such as ant colony optimization. This method has been combined with a Monte Carlo approach, developing a new algorithm for assessing both main and interaction terms when analyzing the influence of experimental factors through a Plackett-Burman design of experiments. The results for both simulated and analytically relevant experimental systems show excellent agreement with previous approaches, highlighting the importance of considering potential interactions when conducting a screening search.

DOI: 10.1016/j.talanta.2012.04.025

Cite this paper

@article{Olivieri2012UncoveringII, title={Uncovering interactions in Plackett-Burman screening designs applied to analytical systems. A Monte Carlo ant colony optimization approach.}, author={Alejandro C. Olivieri and Jorge F. Magallanes}, journal={Talanta}, year={2012}, volume={97}, pages={242-8} }