Extraction process optimisation using particle swarm algorithm Online publication date: Sat, 28-Jun-2014
by Madhuri Arya; Kusum Deep
International Journal of Artificial Intelligence and Soft Computing (IJAISC), Vol. 4, No. 1, 2014
Abstract: In this paper, particle swarm optimisation (PSO) is applied for optimising the yields of three useful bioactive compounds in the extract of the fruits of Gardenia, a Chinese herb. Two of these compounds are used as natural colouring agents in food and medicine whereas the third, having high anti-oxidant capacity, is used in drugs for the cure of many diseases. The yields of these compounds in Gardenia extract are dependent on three process variables, namely, extraction temperature, extraction time and ethanol concentration, defining the extraction conditions. In this study, PSO is used to determine the optimum extraction conditions, i.e., the values of the three process variables that will produce optimum yields of the three bioactive compounds. Most of the work in this direction has used response surface methodology. But the results of our simulations show that PSO is better suited for the problem at hand.
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