DOIONLINE 
DOIONLINE Publish In |
International Journal of Advances in Science, Engineering and Technology(IJASEAT)-IJASEAT |
 Journal Home Volume Issue |
||||||||
Issue |
Volume-5, Issue-4, Spl. Iss-1 ( Nov, 2017 ) | |||||||||
Paper Title |
Nested Hybrid Differential Evolution For Bi-Level Mixed-Integer Optimization in Metabolic Networks | |||||||||
Author Name |
Feng-Sheng Wang | |||||||||
Affilition |
Department of Chemical Engineering, National Chung Cheng University, Taiwan | |||||||||
Pages |
52-55 | |||||||||
Abstract |
Numerous bi-level optimization methods have been used to determine optimal strain designs for the genomescale metabolic networks of bacteria. Such bi-level optimization problems are generally reduced to single-level problems using strong duality theory. However, this approach can exponentially increase computation time because the number of decision variables is increased, and that a growth-coupled production strain cannot be guaranteed. This study is to introduce the two-population nested hybrid differential evolution algorithm that can easily solve the bi-level optimization problem to achieve a set of growth-coupled production strains. It is tested through the simulation of the iAF1260 metabolic network of E. coli. Keywords - Bi-level Optimization, Differential Evolution, Metabolic Engineering, Evolutionary optimization | |||||||||
| View Paper | ||||||||||
