Genetic algorithm optimization of supercritical fluid extraction of nimbin from neem seeds

Abstract

The subject of this study is to optimize supercritical extraction of nimbin from neem seeds using a Genetic Algorithm (GA) technique. In order to investigate the effect of parameters on nimbin extraction yield, a partial differential equation model based on mass conservation was developed and solved numerically. The results were successfully validated and a parameter estimation problem that employs laboratory experimental data was solved. Using this validated model and the optimized set of parameters in the model, another problem was formulated with the aim of optimizing the extraction process. Profit was set as the objective function. Using a GA optimization algorithm, it was found that profit achieves its maximum when T = 305 k, P = 200 bar, carbon dioxide flow rate = 0.967 cm3/min and dp = 0.1431 cm. The ability of the GA algorithm in optimizing the process was compared with a traditional Gradient Search (GS) optimization technique. THE GA technique proved to be a more efficient technique; especially when considering computational effort in reaching an optimal solution.