Multi-objective optimization of fed-batch bioreactor for lysine production

Ashish M. Gujarathi*, Swaprabha P. Patel, Badria Al Siyabi

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Lysine production via the fermentation process is one of the most economical production routes that involves simultaneous conflicting objectives. Two multi-objective differential evolution algorithms MODE-III and MODE-III-IMS are used to obtain the optimal control parameters of the lysine bioreactor. Two conflicting objectives, namely yield and productivity, are studied. Singular and constant feeding policies using both algorithms are studied, and respective Pareto fronts are reported. Tournament selection and penalty constraint handling methods are used, and their performances are compared for both algorithms. The higher bound of feeding rate (2.0 L/s) is found to be the best feeding rate compared to other feeding rates. The MODE-III-IMS algorithm converged to the Pareto front faster than the MODE-III algorithm. The COPRAS method is used to carry out the Pareto ranking, and the best optimal solution is reported. The decision tree method is used to predict and report the best optimal solution with acceptable accuracy.

Original languageEnglish
Pages (from-to)2071-2080
Number of pages10
JournalMaterials and Manufacturing Processes
Volume38
Issue number16
DOIs
Publication statusPublished - May 27 2023

Keywords

  • Biochemical
  • Bioreactor
  • Constraints
  • Fed-batch
  • Lysine
  • MODE
  • Machine learning
  • Pareto ranking
  • Productivity
  • Yield

ASJC Scopus subject areas

  • General Materials Science
  • Mechanics of Materials
  • Mechanical Engineering
  • Industrial and Manufacturing Engineering

Cite this