TY - JOUR
T1 - Optimization of biochemical systems production using combination of newton method and particle swarm optimization
AU - Ismail, Mohd Arfian
AU - Mezhuyev, Vitaliy
AU - Darmawan, Irfan
AU - Kasim, Shahreen
AU - Mohamad, Mohd Saberi
AU - Ibrahim, Ashraf Osman
N1 - Publisher Copyright:
© 2019 International Journal on Advanced Science Engineering Information Technology.
PY - 2019
Y1 - 2019
N2 - 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.
AB - 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.
KW - Biochemical systems
KW - Computational intelligence
KW - Newton method
KW - Optimization
KW - Particle swarm optimization
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UR - http://www.scopus.com/inward/citedby.url?scp=85068425109&partnerID=8YFLogxK
U2 - 10.18517/ijaseit.9.3.4987
DO - 10.18517/ijaseit.9.3.4987
M3 - Article
AN - SCOPUS:85068425109
SN - 2088-5334
VL - 9
SP - 753
EP - 758
JO - International Journal on Advanced Science, Engineering and Information Technology
JF - International Journal on Advanced Science, Engineering and Information Technology
IS - 3
ER -