Naslov
Computer assisted gradient elution optimization in ion chromatography II. Genetic algorithm based approach

Autori
Bolanča, Tomislav ; Novak, Mirjana ; Rogošić, Marko ; Ukić, Šime

Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni

Izvornik
Abstract Book ISC 2012 29th International Symposium on Chromatography / Buszewski, Bogusław ; Kowalska, Joanna - Toruń : Wydawnictwo Adam Marszałek, 2012, 255-255

ISBN
978-83-7780-440-7

Skup
29th International Symposium on Chromatography & 18th International Symposium on Separation Sciences

Mjesto i datum
Toruń, Poljska, 09.09.2012. - 13.09.2012

Vrsta sudjelovanja
Poster

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
ion chromatography; gradient elution; optimization; genetic algorithm

Sažetak
Application of Pareto optimality principles for computer assisted gradient elution optimization in ion chromatography allows multi-objective optimization avoiding the use of weighted combinations of the objective functions defining each dimension in the responses space. This enables managing situations with two or more objective functions representing conflicting criteria without the need of using more or less arbitrarily assigned weighting coefficients. However, the suitable computer assisted optimization methodology is required in order to process large set of solutions rather than a unique solution. This work focuses on application of genetic algorithm for gradient elution optimization in ion chromatography. Developed optimization algorithm uses gradient elution retention model based on crossing the retention information from isocratic elution mode. The number of optimal gradient steps was commented in terms of efficient chromatography related to calculation speed and usability obtained using conventional personal computer. Different experimental design strategies were tested for setting initial searching conditions, followed by optimization of genetic algorithm parameters (selection algorithm, crossover and mutation function, stopping criteria). Predicted optimal conditions were evaluated and obtained feedback allowed the fine tuning of the computer routine. Finally, it is shown that developed genetic algorithm based approach offers effective alternative to the field of gradient optimization in ion chromatography.

Izvorni jezik
Engleski

Znanstvena područja
Kemija, Kemijsko inženjerstvo

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