In this work, an integrated scheduling and Economic Nonlinear Model Predictive Control (ENMPC) framework is designed for the optimal operation of a fermentation process comprising multiple fed-batch fermenters operating in parallel, using as a case study a lignocellulosic biomass biorefinery that produces bioethanol, a promising but limited alternative to fossil fuels. The integrated scheduler and controller aim to find optimal decisions among staggered reactors operating simultaneously, being able to imitate continuous operation. Overall, the proposed operation strategy is able to economically distribute feed flows and yeast used in each reactor, by considering coupled scheduling and control interactions, and user defined constraints, e.g., avoiding excessively large feed flow changes. The yeast, the non-constant substrate feeding policies, and the optimal fed-batch times that maximize profit and reject feedstock composition disturbances are obtained. The results show that, in contrast to traditional scheduling and constant feeding rate policies, variable feeding rates integrated with scheduling decisions may lead to reductions in operating costs, while yielding a similar ethanol productivity, which could be a step forward to achieving large-scale sustainable bioethanol production in global decarbonization efforts.