Mohd Arfian, Ismail and Mezhuyev, Vitaliy and Safaai, Deris and Mohd Saberi, Mohamad and Shahreen, Kasim and Saedudin, Rd Rohmat (2017) Multi-objective Optimization of Biochemical System Production Using an Improve Newton Competitive Differential Evolution Method. International Journal on Advanced Science, Engineering and Information Technology, 7 (4-2). pp. 1535-1542. ISSN 2088-5334. (Published)
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Abstract
In this paper, an improved 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 contains many components. In addition, the multi-objective problem also needs to be considered. Due to that, this study proposed and improved a 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 performs well compared to other works.
| Item Type: | Article |
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| Uncontrolled Keywords: | Newton method; differential evolution algorithm; competitive co-evolutionary algorithm; biochemical system |
| Subjects: | Q Science > QA Mathematics > QA76 Computer software |
| Faculty/Division: | Faculty of Computer System And Software Engineering |
| Depositing User: | Dr. Mohd Arfian Ismail |
| Date Deposited: | 30 Jan 2018 04:03 |
| Last Modified: | 27 Feb 2018 01:02 |
| URI: | http://umpir.ump.edu.my/id/eprint/20028 |
| Download Statistic: | View Download Statistics |
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