Optimizing pigment production from agricultural waste using metaheuristic-based algorithms

Due to the uncontrolled industrial applications of synthetic pigments that can cause a serious hazard to human health and the environment, the scientific community skewed towards natural colors. The simplest and efficient method to increase pigment production is by manipulating the medium. Among cla...

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Main Author:	Suhaimi, Siti Nurulasilah
Format:	Thesis
Language:	English
Published:	2022
Subjects:	QA75 Electronic computers Computer science
Online Access:	http://eprints.utm.my/id/eprint/101521/1/SitiNurulasilahSuhaimiPSC2022.pdf.pdf
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id	my-utm-ep.101521
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spelling	my-utm-ep.1015212023-06-21T10:29:22Z Optimizing pigment production from agricultural waste using metaheuristic-based algorithms 2022 Suhaimi, Siti Nurulasilah QA75 Electronic computers. Computer science Due to the uncontrolled industrial applications of synthetic pigments that can cause a serious hazard to human health and the environment, the scientific community skewed towards natural colors. The simplest and efficient method to increase pigment production is by manipulating the medium. Among classical and statistical methods, one factor at a time and response surface methodology (RSM) is the most widely used in medium optimization. However, the main drawback of these methods is tedious wet experiments need to be conducted to predict the output for a new input data and prior to data processing and analytic for decision making. In the past few years, the rapid advances in the field of metaheuristic optimization algorithm have provided a solution in optimization problems. In this study, metaheuristic optimization scheme, together with the mathematical model which is regression analysis have been implemented to minimize time and cost of wet-lab experiments by increasing the pigment productions using the proposed compact experiments. Moreover, the predictive optimization performance and sensitivity analysis of metaheuristic algorithm have been evaluated to validate the results, and the authenticity has been proven by wet laboratory experiments. Analysis of the optimization showed that the percentage improvement for the proposed compact experiment which is particle swarm optimization (PSO) model improved from RSM model by 1.32%, while the percentage improvement for all compact experiments was better than multiple polynomial model (MPR) model with the highest PSO percentage of 2.0507%. Hence, the experimental findings revealed that, the metaheuristic-based approach successfully predicted the optimum fermentation parameters condition and concentration with better achievement on pigment production by using proposed compact experiment. 2022 Thesis http://eprints.utm.my/id/eprint/101521/ http://eprints.utm.my/id/eprint/101521/1/SitiNurulasilahSuhaimiPSC2022.pdf.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:150789 phd doctoral Universiti Teknologi Malaysia Faculty of Engineering - School of Computing
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	QA75 Electronic computers Computer science
spellingShingle	QA75 Electronic computers Computer science Suhaimi, Siti Nurulasilah Optimizing pigment production from agricultural waste using metaheuristic-based algorithms
description	Due to the uncontrolled industrial applications of synthetic pigments that can cause a serious hazard to human health and the environment, the scientific community skewed towards natural colors. The simplest and efficient method to increase pigment production is by manipulating the medium. Among classical and statistical methods, one factor at a time and response surface methodology (RSM) is the most widely used in medium optimization. However, the main drawback of these methods is tedious wet experiments need to be conducted to predict the output for a new input data and prior to data processing and analytic for decision making. In the past few years, the rapid advances in the field of metaheuristic optimization algorithm have provided a solution in optimization problems. In this study, metaheuristic optimization scheme, together with the mathematical model which is regression analysis have been implemented to minimize time and cost of wet-lab experiments by increasing the pigment productions using the proposed compact experiments. Moreover, the predictive optimization performance and sensitivity analysis of metaheuristic algorithm have been evaluated to validate the results, and the authenticity has been proven by wet laboratory experiments. Analysis of the optimization showed that the percentage improvement for the proposed compact experiment which is particle swarm optimization (PSO) model improved from RSM model by 1.32%, while the percentage improvement for all compact experiments was better than multiple polynomial model (MPR) model with the highest PSO percentage of 2.0507%. Hence, the experimental findings revealed that, the metaheuristic-based approach successfully predicted the optimum fermentation parameters condition and concentration with better achievement on pigment production by using proposed compact experiment.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Suhaimi, Siti Nurulasilah
author_facet	Suhaimi, Siti Nurulasilah
author_sort	Suhaimi, Siti Nurulasilah
title	Optimizing pigment production from agricultural waste using metaheuristic-based algorithms
title_short	Optimizing pigment production from agricultural waste using metaheuristic-based algorithms
title_full	Optimizing pigment production from agricultural waste using metaheuristic-based algorithms
title_fullStr	Optimizing pigment production from agricultural waste using metaheuristic-based algorithms
title_full_unstemmed	Optimizing pigment production from agricultural waste using metaheuristic-based algorithms
title_sort	optimizing pigment production from agricultural waste using metaheuristic-based algorithms
granting_institution	Universiti Teknologi Malaysia
granting_department	Faculty of Engineering - School of Computing
publishDate	2022
url	http://eprints.utm.my/id/eprint/101521/1/SitiNurulasilahSuhaimiPSC2022.pdf.pdf
_version_	1776100717802553344

Optimizing pigment production from agricultural waste using metaheuristic-based algorithms

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