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A Hybrid of Optimization Method for Multi-Objective Constraint Optimization of Biochemical System Production

Mohd Arfian, Ismail and Safaai, Deris and Mohd Saberi, Mohamad and Mohd Adham, Isa and Afnizanfaizal, Abdullah and Muhammad Akmal, Remli and Mohi-Aldeen, Shayma Mustafa (2015) A Hybrid of Optimization Method for Multi-Objective 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)

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Abstract

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.

Item Type: Article
Uncontrolled Keywords: Newton Method, Strength Pareto Evolutionary Algorit hm, Genetic Algorithm, Cooperative Co- evolutionary Algorithm, Biochemical System
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty/Division: Faculty of Computer System And Software Engineering
Depositing User: Dr. Mohd Arfian Ismail
Date Deposited: 17 Mar 2016 07:56
Last Modified: 27 Mar 2018 03:40
URI: http://umpir.ump.edu.my/id/eprint/11776
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