A REVIEW OF GENETIC ALGORITHMS AND ITS APPLICATIONS IN CHEMICAL ENGINEERING RESEARCH

This paper presents a review of Genetic Algorithms (GAs) and its applications within the field of Chemical Engineering. The primary applications of GAs in Chemical Engineering date back to the 1970s, and within the last decades, they have b een more and more often used to solve various complex problems, even when the objective functions don't possess properties like continuity, differentiability and so on. These algorithms manipulate and maintain a set or population of solutions and implement a “survival of the fittest” strategy in their search for better solutions. GAs are very helpful for the optimization and variable selection in modeling and calibration due to the strong effect of the relationship between presence/absence of variables in a calibration model and the prediction ability of the model itself. This review is an outline of the concept of GA and in fact, it does not present all applications of Genetic Algorithms to Chemical Engineering problems; its goal is to rather point out to t he researchers, the important fields of application of GAs along with providing a list of references on the topic