Multi-objective optimization of glycopeptide antibiotic production in batch and fed batch processes

Fermentation optimization involves potentially conflicting multiple objectives such as product concentration and production media cost. Simultaneous optimization of these objectives would result in a multiobjective optimization problem, which is characterized by a set of multiple solutions, knows as pareto optimal solutions. These solutions gives flexibility in evaluating the trade-offs and selecting the most suitable operating policy. Here, ε-constraint approach was used to generate the pareto solutions for two objectives: product concentration and product per unit cost of media, for batch and fed batch operations using process model for Amycolatopsis balhimycina, a glycopeptide antibiotic producer. This resulted in a set of several pareto optimal solutions with the two objectives ranging from (0.75 g l⁻¹, 3.97 g $^-1) to (0.44 g l⁻¹, 5.19 g $^-1) for batch and from (1.5 g l⁻¹, 5.46 g $^-1) to (1.1 g l⁻¹, 6.34 g $^-1) for fed batch operations. One pareto solution each for batch and for fed batch mode was experimentally validated.