Multi-criteria analysis of cell-recycle based continuous lactic acid production process

Abstract

This study focuses on the optimization of the cell-recycle based continuous lactic acid (LA) fermentation production process with the estimation of improved kinetic parameters. The non-dominated sorting genetic algorithm II (NSGA-II) is used considering seven variables and five imposed constraints for multi-objective optimization (MOO) study. Three objectives namely LA productivity, substrate conversion, and yield are formed for the maximization purpose. Three different cases are constructed by using a combination of two bi-objectives and one tri-objective optimization problem, and the modified differential evolution (MDE) algorithm is used to individually optimize each case. Pareto ranking is carried out for MOO, and the best optimal solution is determined using the technique for order preference by similarity to the ideal solution (TOPSIS) method. The highest value of volumetric productivity of LA (184.363 kg/m3.h) is reported in case-4a. The highest yield (1.176) is reported in case-2, while the highest substrate conversion (0.963) is reported in case-1.