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.
| Original language | English |
|---|---|
| Pages (from-to) | 502-513 |
| Number of pages | 12 |
| Journal | Journal of Theoretical and Applied Information Technology |
| Volume | 81 |
| Issue number | 3 |
| Publication status | Published - Nov 30 2015 |
| Externally published | Yes |
Keywords
- Biochemical system
- Cooperative coevolutionary algorithm
- Genetic algorithm
- Newton method
- Strength pareto evolutionary algorithm
ASJC Scopus subject areas
- Theoretical Computer Science
- General Computer Science