The design and optimization of a coupled distillation system is a non-linear and multivariable problem. The complexity of this kind of problem leads to the high difficulty for solving it. This paper addresses the application of genetic algorithms to the optimization of intensified distillation systems for quaternary distillations. For that purpose, we used a multi-objective genetic algorithm with restrictions, written in Matlab TM coupled to process simulator Aspen Plus TM for the evaluation of the objective function.

Red beets in Mexico are used in the colorants industry, but their juice bagasse (RBB) can be carbohydrates for ethanol production. The present study aims to the pretreatment of bagasse of red beet using acid (H2SO4) and alkali (NaOH) to improve the availability of sugars. Also, describe quantitatively in the hydrolysates the microbial growth, substrate consumption, and ethanol production with simulation using data kinetics of red beet and logistic, Pirt, and Luedeking-Piret equations. Experiments with H2SO4 at sterilization conditions resulted in lower phenolic formation and increased hydrolysis to 32 %. Logistic, Pirt, and Luedeking-Piret equations were used to quantitatively describe the hydrolysates the microbial growth, substrate consumption, and ethanol production, respectively. In the alkali treatment, a significant mean difference was found (p < 0.05) in substrate mass and reaction time. The maximum yield of 38 g/L of total sugars at 72 h of reaction was obtained from 6 g RBB and H2SO4 at 0.5 N. The ethanol yield was 15 to 18 g/L representing about 78 to 92 % of the theoretical yield.