Mohd Arfian, Ismail and Mezhuyev, Vitaliy and Irfan, Darmawan and Shahreen, Kasim and Mohd Saberi, Mohamad and Ashraf Osman, Ibrahim (2019) Optimization of biochemical systems production using combination of newton method and particle swarm optimization. International Journal on Advanced Science, Engineering and Information Technology, 9 (3). pp. 753-758. ISSN 2088-5334. (Published)
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Abstract
In the presented paper, an improved method that combines the Newton method with Particle Swarm Optimization (PSO) algorithm to optimize the production of biochemical systems was discussed and presented in detail. The optimization of the biochemical system's production became difficult and complicated when it involves a large size of biochemical systems that have many components and interaction between chemical. Also, two objectives and several constraints make the optimization process difficult. To overcome these situations, the proposed method was proposed by treating the biochemical systems as a nonlinear equations system and then optimizes using PSO. The proposed method was proposed to improve the biochemical system's production and at the same time reduce the total of chemical concentration involves. In the proposed method, the Newton method was used to deal with nonlinear equations system, while the PSO algorithm was utilized to fine-tune the variables in nonlinear equations system. The main reason for using the Newton method is its simplicity in solving the nonlinear equations system. The justification of choosing PSO algorithm is its direct implementation and effectiveness in the optimization process. In order to evaluate the proposed method, two biochemical systems were used, which were E.coli pathway and S. cerevisiae pathway. The experimental results showed that the proposed method was able to achieve the best result as compared to other works.
| Item Type: | Article |
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| Additional Information: | Indexed by Scopus |
| Uncontrolled Keywords: | Newton method; Particle swarm optimization; Optimization; Biochemical systems; Computational intelligence |
| Subjects: | Q Science > Q Science (General) Q Science > QA Mathematics T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Faculty/Division: | Faculty of Computer System And Software Engineering |
| Depositing User: | Mrs Norsaini Abdul Samat |
| Date Deposited: | 21 Nov 2019 01:32 |
| Last Modified: | 21 Nov 2019 01:32 |
| URI: | http://umpir.ump.edu.my/id/eprint/25614 |
| Download Statistic: | View Download Statistics |
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