Title: Extraction process optimisation using particle swarm algorithm
Authors: Madhuri Arya; Kusum Deep
Addresses: Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand 247667, India ' Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand 247667, India
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.
Keywords: particle swarm optimisation; PSO; extraction optimisation; natural colorants; natural anti-oxidants; bio-active compounds; compund extraction; gardenia extraction; food safety; swarm intelligence; artificial intelligence; soft computing; extraction temperature; extraction time; ethanol concentration; process variables; simulation.
International Journal of Artificial Intelligence and Soft Computing, 2014 Vol.4 No.1, pp.29 - 40
Received: 14 Feb 2013
Accepted: 09 Apr 2013
Published online: 28 Jun 2014 *