A Hybrid of Optimization Method for Multiobjective Constraint Optimization Of Biochemical System Production

In this paper, an advance method for multi-objective constraint optimization method of biochemical system production was proposed and discussed in detail. The proposed method combines Newton method, Strength Pareto Evolutionary Algorithm (SPEA) and Cooperative Co-evolutionary Algorithm (CCA). The m...

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Main Authors: Mohd Arfian, Ismail, Safaai, Deris, Mohd Saberi, Mohamad, Mohd Adham, Isa, Afnizanfaizal, Abdullah, Muhammad Akmal, Remli, Shayma, Mustafa Mohi-Aldeen
Format: Article
Language:English
Published: JATIT 2015
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Online Access:http://umpir.ump.edu.my/id/eprint/11864/1/A%20Hybrid%20Of%20Optimization%20Method%20For%20Multiobjective%20Constraint%20Optimization%20Of%20Biochemical%20System%20Production.pdf
http://umpir.ump.edu.my/id/eprint/11864/
http://www.jatit.org/volumes/Vol81No3/14Vol81No3.pdf
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Institution: Universiti Malaysia Pahang
Language: English
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spelling my.ump.umpir.118642018-03-27T03:44:11Z http://umpir.ump.edu.my/id/eprint/11864/ A Hybrid of Optimization Method for Multiobjective Constraint Optimization Of Biochemical System Production Mohd Arfian, Ismail Safaai, Deris Mohd Saberi, Mohamad Mohd Adham, Isa Afnizanfaizal, Abdullah Muhammad Akmal, Remli Shayma, Mustafa Mohi-Aldeen QA76 Computer software In this paper, an advance method for multi-objective constraint optimization method of biochemical system production was proposed and discussed in detail. The proposed method combines Newton method, Strength Pareto Evolutionary Algorithm (SPEA) and Cooperative Co-evolutionary Algorithm (CCA). The main objective of the proposed method was to improve the desired production and at the same time to reduce the total of component concentrations involved in producing the best result. The proposed method starts with Newton method by treating the biochemical system as a non-linear equations system. Then, Genetic Algorithm (GA) in SPEA and CCA were used to represent the variables in non-linear equations system into multiple sub-chromosomes. The used of GA was to improve the desired production while CCA to reduce the total of component concentrations involved. The effectiveness of the proposed method was evaluated using two benchmark biochemical systems and the experimental results showed that the proposed method was able to generate the highest results compare to other existing works. JATIT 2015 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/11864/1/A%20Hybrid%20Of%20Optimization%20Method%20For%20Multiobjective%20Constraint%20Optimization%20Of%20Biochemical%20System%20Production.pdf Mohd Arfian, Ismail and Safaai, Deris and Mohd Saberi, Mohamad and Mohd Adham, Isa and Afnizanfaizal, Abdullah and Muhammad Akmal, Remli and Shayma, Mustafa Mohi-Aldeen (2015) A Hybrid of Optimization Method for Multiobjective Constraint Optimization Of Biochemical System Production. Journal of Theoretical and Applied Information Technology, 81 (3). pp. 502-513. ISSN 1992-8645 (print); 817-3195 (online) http://www.jatit.org/volumes/Vol81No3/14Vol81No3.pdf
institution Universiti Malaysia Pahang
building UMP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang
content_source UMP Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic QA76 Computer software
spellingShingle QA76 Computer software
Mohd Arfian, Ismail
Safaai, Deris
Mohd Saberi, Mohamad
Mohd Adham, Isa
Afnizanfaizal, Abdullah
Muhammad Akmal, Remli
Shayma, Mustafa Mohi-Aldeen
A Hybrid of Optimization Method for Multiobjective Constraint Optimization Of Biochemical System Production
description In this paper, an advance method for multi-objective constraint optimization method of biochemical system production was proposed and discussed in detail. The proposed method combines Newton method, Strength Pareto Evolutionary Algorithm (SPEA) and Cooperative Co-evolutionary Algorithm (CCA). The main objective of the proposed method was to improve the desired production and at the same time to reduce the total of component concentrations involved in producing the best result. The proposed method starts with Newton method by treating the biochemical system as a non-linear equations system. Then, Genetic Algorithm (GA) in SPEA and CCA were used to represent the variables in non-linear equations system into multiple sub-chromosomes. The used of GA was to improve the desired production while CCA to reduce the total of component concentrations involved. The effectiveness of the proposed method was evaluated using two benchmark biochemical systems and the experimental results showed that the proposed method was able to generate the highest results compare to other existing works.
format Article
author Mohd Arfian, Ismail
Safaai, Deris
Mohd Saberi, Mohamad
Mohd Adham, Isa
Afnizanfaizal, Abdullah
Muhammad Akmal, Remli
Shayma, Mustafa Mohi-Aldeen
author_facet Mohd Arfian, Ismail
Safaai, Deris
Mohd Saberi, Mohamad
Mohd Adham, Isa
Afnizanfaizal, Abdullah
Muhammad Akmal, Remli
Shayma, Mustafa Mohi-Aldeen
author_sort Mohd Arfian, Ismail
title A Hybrid of Optimization Method for Multiobjective Constraint Optimization Of Biochemical System Production
title_short A Hybrid of Optimization Method for Multiobjective Constraint Optimization Of Biochemical System Production
title_full A Hybrid of Optimization Method for Multiobjective Constraint Optimization Of Biochemical System Production
title_fullStr A Hybrid of Optimization Method for Multiobjective Constraint Optimization Of Biochemical System Production
title_full_unstemmed A Hybrid of Optimization Method for Multiobjective Constraint Optimization Of Biochemical System Production
title_sort hybrid of optimization method for multiobjective constraint optimization of biochemical system production
publisher JATIT
publishDate 2015
url http://umpir.ump.edu.my/id/eprint/11864/1/A%20Hybrid%20Of%20Optimization%20Method%20For%20Multiobjective%20Constraint%20Optimization%20Of%20Biochemical%20System%20Production.pdf
http://umpir.ump.edu.my/id/eprint/11864/
http://www.jatit.org/volumes/Vol81No3/14Vol81No3.pdf
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