Fuzzy optimization for a batch simultaneous saccharification and co-fermentation process by hybrid differential evolution

The crisp and fuzzy optimization approaches were introduced to design an optimal temperature control policy for a batch process of simultaneous saccharification and cofermentation (SSCF) to produce ethanol from lignocellulose using the enzymes and the recombinant strain Saccharomyces yeast 1400 (pLNH33). The goal of the optimal design herein is to find the optimal temperature, initial lignocellulosic concentration, and fermentation time that maximize the ethanol productivity under the constraints of follow-up separation specifications. The interactive crisp and fuzzy optimization methods towards were respectively applied to solve the trade-off optimization problems in order to obtain a compromised design. The fuzzy goal attainment approach can more flexibly obtain a comprehensive design in comparison to the crisp optimization. Both crisp and fuzzy optimization could be efficiently solved by hybrid differential evolution.