초록
<P><B>Abstract</B></P> <P>A multi-objective optimization of simultaneous saccharification and fermentation process for cellulosic ethanol production was carried out to simultaneously maximize the ethanol yield/cellulose conversion and minimize the enzyme consumption by manipulating the initial sugar concentrations, and cellulose and enzyme loadings. The study was based on an experimentally verified kinetic model. Several bi-objective optimization problems with different combinations of objectives and constraints were solved by a controlled elitist genetic algorithm, a variant of the non-dominated sorting genetic algorithm II (NSGA-II). The optimum operating conditions were verified by experiments. There was significant performance improvement in terms of ethanol yield, cellulose conversion and enzyme loading. An overall 40% reduction of enzyme consumption per ethanol produced was attained at the same ethanol yield (32%) of a non-optimized process. However, the optimum conditions are highly sensitive to the selected kinetic model and associated kinetic parameters therefore, selection of the appropriate kinetic model is critical.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Multi-objective optimization of SSF based on mechanistic kinetic model. </LI> <LI> Interactions of substrate concentration and enzyme loading on SSF. </LI> <LI> Enhancement of SSF performance by optimization and experimental verification. </LI> </UL> </P>