DOI : https://doi.org/10.18517/ijaseit.7.4-2.3388

Multi-objective Optimization of Biochemical System Production Using an Improve Newton Competitive Differential Evolution Method

Mohd Arfian Ismail (1), Vitaliy Mezhuyev (2), Safaai Deris (3), Mohd Saberi Mohamad (4), Shahreen Kasim (5), Rd Rohmat Saedudin (6)
(1) Faculty of Computer Systems and Software Engineering, Universiti Malaysia Pahang, Pahang, Malaysia
(2) Faculty of Computer Systems and Software Engineering, Universiti Malaysia Pahang, Pahang, Malaysia
(3) Faculty of Creative Technology and Heritage, Universiti Malaysia Kelantan, Kelantan, Malaysia
(4)
(5) Soft Computing and Data Mining Centre, Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn, Johor, Malaysia
(6) School of Industrial Engineering, Telkom University, 40257 Bandung, West Java, Indonesia
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How to cite (IJASEIT) :
Ismail, Mohd Arfian, et al. “Multi-Objective Optimization of Biochemical System Production Using an Improve Newton Competitive Differential Evolution Method”. International Journal on Advanced Science, Engineering and Information Technology, vol. 7, no. 4-2, Sept. 2017, pp. 1535-42, doi:10.18517/ijaseit.7.4-2.3388.
Citation Format :
In this paper, an improve method of multi-objective optimization for biochemical system production is presented and discussed in detail. The optimization process of biochemical system production become hard and difficult when involved a large biochemical system that contain with many components. In addition, the multi-objective problem also need to be considered. Due to that, this study proposed and improve method that comprises with Newton method, differential evolution algorithm (DE) and competitive co-evolutionary algorithm(ComCA). The aim of the proposed method is to maximize the production and simultaneously minimize the total amount of chemical concentrations involves. The operation of the proposed method starts with Newton method by dealing with biochemical system production as a nonlinear equations system. Then DE and ComCA are used to represent the variables in nonlinear equation system and tune the variables in order to find the best solution. The used of DE is to maximize the production while ComCA is to minimize the total amount of chemical concentrations involves. The effectiveness of the proposed method is evaluated using two benchmark biochemical systems and the experimental results show that the proposed method perform well compared to other works.
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