A multi-objective micro-scale optimization strategy for fermentation processes was proposed to achieve optimal operation on the basis of a dynamic metabolic flux analysis (DMFA) model. According to different dynamic characteristics

the strategy divided a fermentation process into two stages of cell growth and product synthesis

in which objective functions and constraints were designed from micro metabolic flux and pathways. Multi-objective particle swarm optimization (MOPSO) was employed as key algorithm to find operation trajectory. The strategy was applied to simulation of penicillin fermentation for optimizing acceleration rate of feed stock and pH trajectory. The results showed that terminal product concentration was increased by 3.26% and total feed amount was decreased by 0.6 L

indicating effectiveness of the strategy.