We report on the performance of three classes of evolutionary algorithms (genetic algorithms (GA), evolution strategies (ES) and covariance matrix adaptation evolution strategy (CMA-ES)) as a means to enhance searches in the method development spaces of 1D- and 2D-chromatography. After optimisation of the design parameters of the different algorithms, they were benchmarked against the performance of a plain grid search. It was found that all three classes significantly outperform the plain grid search, especially in terms of the number of search runs needed to achieve a given separation quality. As soon as more than 100 search runs are needed, the ES algorithm clearly outperforms the GA and CMA-ES algorithms, with the latter performing very well for short searches (<50 search runs) but being susceptible to convergence to local optima for longer searches. It was also found that the performance of the ES and GA algorithms, as well as the grid search, follow a hyperbolic law in the large search run number limit, such that the convergence rate parameter of this hyperbolic function can be used to quantify the difference in required number of search runs for these algorithms. In agreement with one's physical expectations, it was also found that the general advantage of the GA and ES algorithms over the grid search, as well as their mutual performance differences, grow with increasing difficulty of the separation problem.
Huygens, B, Efthymiadis, K, Nowe, A & Desmet, G 2020, 'Application of evolutionary algorithms to optimise one- and two-dimensional gradient chromatographic separations', Journal of Chromatography. A, vol. 1628, 461435. https://doi.org/10.1016/j.chroma.2020.461435, https://doi.org/10.1016/j.chroma.2020.461435
Huygens, B., Efthymiadis, K., Nowe, A., & Desmet, G. (2020). Application of evolutionary algorithms to optimise one- and two-dimensional gradient chromatographic separations. Journal of Chromatography. A, 1628, Article 461435. https://doi.org/10.1016/j.chroma.2020.461435, https://doi.org/10.1016/j.chroma.2020.461435
@article{981f091ebd6d49dba77ffbdc82cb0a83,
title = "Application of evolutionary algorithms to optimise one- and two-dimensional gradient chromatographic separations",
abstract = "We report on the performance of three classes of evolutionary algorithms (genetic algorithms (GA), evolution strategies (ES) and covariance matrix adaptation evolution strategy (CMA-ES)) as a means to enhance searches in the method development spaces of 1D- and 2D-chromatography. After optimisation of the design parameters of the different algorithms, they were benchmarked against the performance of a plain grid search. It was found that all three classes significantly outperform the plain grid search, especially in terms of the number of search runs needed to achieve a given separation quality. As soon as more than 100 search runs are needed, the ES algorithm clearly outperforms the GA and CMA-ES algorithms, with the latter performing very well for short searches (<50 search runs) but being susceptible to convergence to local optima for longer searches. It was also found that the performance of the ES and GA algorithms, as well as the grid search, follow a hyperbolic law in the large search run number limit, such that the convergence rate parameter of this hyperbolic function can be used to quantify the difference in required number of search runs for these algorithms. In agreement with one's physical expectations, it was also found that the general advantage of the GA and ES algorithms over the grid search, as well as their mutual performance differences, grow with increasing difficulty of the separation problem.",
keywords = "Evolutionary algorithms, Gradient elution, Liquid chromatography, Method development, Multi-dimensional chromatography",
author = "Bram Huygens and Kyriakos Efthymiadis and Ann Nowe and Gert Desmet",
note = "Funding Information: BH and GD gratefully acknowledge the FWO-FRNS grant EOS nr. 30897864. Publisher Copyright: {\textcopyright} 2020 Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; 16th International Symposium on Hyphenated Techniques in Chromatography and Separation Technology, HTC-16 ; Conference date: 29-01-2020 Through 31-01-2020",
year = "2020",
month = sep,
day = "27",
doi = "10.1016/j.chroma.2020.461435",
language = "English",
volume = "1628",
journal = "Journal of Chromatography. A",
issn = "0021-9673",
publisher = "Elsevier",
url = "https://kuleuvencongres.be/htc16",
}