Genetic algorithm optimization of supercritical fluid extraction of nimbin from neem seeds
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...
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my.utm.146322011-09-30T15:16:05Z http://eprints.utm.my/id/eprint/14632/ Genetic algorithm optimization of supercritical fluid extraction of nimbin from neem seeds Zahedi, G. Elkamel, A. Lohi, A. TP Chemical technology 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. Elsevier BV 2010 Article PeerReviewed Zahedi, G. and Elkamel, A. and Lohi, A. (2010) Genetic algorithm optimization of supercritical fluid extraction of nimbin from neem seeds. Journal of Food Engineering, 97 (2). pp. 127-134. ISSN 02608774 http://dx.doi.org/10.1016/j.jfoodeng.2009.10.001 doi:10.1016/j.jfoodeng.2009.10.001 |
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TP Chemical technology Zahedi, G. Elkamel, A. Lohi, A. Genetic algorithm optimization of supercritical fluid extraction of nimbin from neem seeds |
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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. |
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Article |
author |
Zahedi, G. Elkamel, A. Lohi, A. |
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Zahedi, G. Elkamel, A. Lohi, A. |
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Zahedi, G. |
title |
Genetic algorithm optimization of supercritical fluid extraction of nimbin from neem seeds |
title_short |
Genetic algorithm optimization of supercritical fluid extraction of nimbin from neem seeds |
title_full |
Genetic algorithm optimization of supercritical fluid extraction of nimbin from neem seeds |
title_fullStr |
Genetic algorithm optimization of supercritical fluid extraction of nimbin from neem seeds |
title_full_unstemmed |
Genetic algorithm optimization of supercritical fluid extraction of nimbin from neem seeds |
title_sort |
genetic algorithm optimization of supercritical fluid extraction of nimbin from neem seeds |
publisher |
Elsevier BV |
publishDate |
2010 |
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http://eprints.utm.my/id/eprint/14632/ http://dx.doi.org/10.1016/j.jfoodeng.2009.10.001 |
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1643646440682029056 |
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13.211869 |