Multi-objective steady-state optimization for a complex bioprocess in glycerol metabolism

Abstract

This paper addresses the multi-objective steady-state optimization of a complex nonlinear system in glycerol metabolism. In the bioconversion system, we consider some mechanisms including the regulation for dha regulon, enzyme-catalytic kinetics, the inhibition of intracellular 3-hydroxypropionaldehyde (3-HPA), and so on. Firstly, we propose several new multi-objective steady-state optimization problems. These problems can simultaneously optimize any two of the following objectives: (1) minimization of the intracellular 3-HPA concentration; (2) maximization of the production rate of extracellular 1,3-propanediol (1,3-PDO); (3) maximization of the conversion rate of extracellular glycerol to extracellular 1,3-PDO; (4) maximization of the conversion rate of extracellular glycerol. Then a hybrid optimization method is proposed to solve the presented complex multi-objective problems. This optimization method couples a deterministic interior point approach and a stochastic genetic algorithm in the framework of normal-boundary intersection (NBI) method. After solving the proposed multi-objective problems of the addressed bioconversion system, we finally obtain their approximate Pareto optimal sets. The analysis for the attained optimization results is given. And a comparative study is also presented.

Keywords

• Bioprocess
• Steady-state optimization
• Multi-objective
• Iterative algorithm
• Hybrid method