Modeling Gilliland Correlation using Genetic Programming
AbstractThe distillation process is one of the most important processes in industry, especially petroleum refining. Designing a distillation column assesses numerous challenges to the engineer, being a complex process that is approached in various studies. An important component, directly affecting the efficient operation of the column, is the reflux ratio that is correlated with the number of the theoretical stages, a correlation developed and studied by Gililland. The correlation is used in the case of simplified control models of distillation columns and it is a graphical method. However, in many situations, there is the need for an analytical form that adequately approximates the experimental data. There are in the literature different analytical forms which are used taking into account the desired precision. The present article attempts to address this problem by using the technique of Genetic Programming, a branch of Evolutionary Algorithms that belongs to Artificial Intelligence, a recently developed technique that has recorded successful applications especially in process modeling. Using an evolutionary paradigm and by evolving a population of solutions or subprograms composed of carefully chosen functions and operators, the Genetic Programming technique is capable of finding the program or relation that fits best the available data.
 J.R. Couper, W.R. Penney, J.R. Fair, S.M. Wallas, Chemical Process Equipment - Second Edition, Elsevier - Gulf Professional Publishing, 2005.
 H.Z. Kister, Distillation Design, McGraw-Hill, 1992.
 J.R. Koza, Genetic Programming - On the Programming of Computer by Means of Natural Selection, MIT Press, 1992.
 M. Mitchell, An Introduction To Genetic Algorithms, MIT Press, 1996.
 N. Paraschiv, Equipment and Programs for Optimal Control of Fractionation Processes, PhD Thesis, "Petroleum-Gas" University of Ploiesti, Ploiesti, 1987.
 N. Paraschiv, An Analytical Form of the Gilliland Graphical Correlation for the Advanced Control of Fractionation Processes, Chemistry Magazine no.7-8, 1990.
 S. Silva, GPLAB - A Genetic Programming Toolbox for Matlab User Manual, ECOS - Evolutionary and Complex Systems Group, University of Coimbra, Portugal, 2007 - accessible from http://gplab.sourceforge.net/index.html.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
ONLINE OPEN ACCES: Acces to full text of each article and each issue are allowed for free in respect of Attribution-NonCommercial 4.0 International (CC BY-NC 4.0.
You are free to:
-Share: copy and redistribute the material in any medium or format;
-Adapt: remix, transform, and build upon the material.
The licensor cannot revoke these freedoms as long as you follow the license terms.
DISCLAIMER: The author(s) of each article appearing in International Journal of Computers Communications & Control is/are solely responsible for the content thereof; the publication of an article shall not constitute or be deemed to constitute any representation by the Editors or Agora University Press that the data presented therein are original, correct or sufficient to support the conclusions reached or that the experiment design or methodology is adequate.