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Abstract: Computer-aided process/solvent design is introduced to find a feasible biocompatible solvent for an extractive fermentation and separation process. The designed biocompatible solvent serves as both the extractant for extractive fermentation and the entrainer for extractive distillation, to yield water-free ethanol. Several goals, such as maximizing production rate and extraction efficiency, and limiting solvent utilization, are simultaneously considered in the optimal solvent design problem. Thus, the design was formulated as a mixed-integer nonlinear optimization problem. A two-phase computational scheme was introduced to solve the problem. The mixed-integer hybrid differential evolution (MIHDE) algorithm was first applied to solve the problem in order to obtain a feasible solution. The feasible solution was then served as an initial starting point for the mixed-integer sequential quadratic programming (MISQP) solver to numerically confirm that the optimal design was achieved. We have compared the crisp and fuzzy approaches to the design problem. The fuzzy goal attainment approach is able to address goal trade-offs and yield an overall satisfactory grade for the problem. [ABSTRACT FROM AUTHOR]

Abstract: In this study, we considered a multi-stage integrated extractive fermentation with cell recycling for ethanol production using the genetically engineered Sacchromyces yeast 1400 (pLNH33), which can utilize glucose and xylose as carbon sources to produce ethanol. Each stage consists of a stirred-tank bioreactor, a cell settler and an extractor. A generalized mathematical model was formulated to express the multi-stage integrated process. The aim of the optimization problem was to obtain the maximum overall productivity and conversions subject to the interval inequality constraints for the residual glucose and xylose concentrations and the total sugar supply. A fuzzy goal attainment method was applied to the multiobjective problem in order to achieve the maximum satisfaction for all design requirements. From the computational results, the integrated extractive fermentation with cell recycling (involving the extraction of ethanol from the extractor in situ to alleviate product inhibition) led to an optimal overall productivity that was 8.0% higher than that obtained by the method of continuous fermentation with cell recycling, and about 13-fold higher than that obtained by the method of continuous fermentation without cell recycling. [Copyright &y& Elsevier]

In this study, crisp and fuzzy multiple-goal optimization approaches are respectively introduced to design an optimal biocompatible solvent to a two-stage extractive fermentation with cell recycling for ethanol production. When designing a biocompatible solvent for the extractive fermentation process, many issues, such as extractive efficiency, conversion, amount of solvent utilized and so on, have to be considered. An interactive multiple-goal design procedure is introduced to determine a trade-off result in order to satisfy such contradicted goals. Both approaches could be iterated to solve the interactive multiple-goal design problem in order to yield a trade-off result. However, the crisp optimization design is a tedious task that requires the designer to provide various pairs of the upper bounds for the design problem to obtain the corresponding solution. The fuzzy optimization approach is able to be trade-off several goals simultaneously and to yield the overall satisfactory grade for the product/process design problem. [Copyright &y& Elsevier]

In this study, crisp and flexible optimization approaches are, respectively, introduced to design an optimal biocompatible solvent for an extractive fermentation process. The optimal design problem is formulated as a mixed-integer nonlinear programming model in which performance requirements of the compounds are reflected in the objective and the constraints. In general, the requirements for the objective and constraints are not rigid; consequently, the flexible or fuzzy optimization approach is applied to soften the rigid requirement for maximization of the extraction efficiency and to consider the mass flow rate and biocompatibility of solvent as the softened inequality constraints to the solvent design problem. Having elicited the membership function for the objective function and the constraint, the optimal solvent design problem can be formulated as a flexible goal attainment problem. Mixed-integer hybrid differential evolution is applied to solve the problem in order to find a satisfactory design. [Copyright &y& Elsevier]

In this study, we consider a two-stage fermenter with cell recycling including an extractor to produce lactic acid. When the extractor was omitted, the proposed process was simplified to two special processes. Under the same operating conditions, we compared the overall lactic acid productivity and glucose conversion for the three processes. The proposed fermentation process was more efficient than the other processes. To simultaneously obtain the maximum productivity and conversion, the problem is formulated as a fuzzy multiobjective optimization problem. The fuzzy decision is introduced to convert the multiobjective fuzzy optimization problem into the fuzzy goal attainment problem. Hybrid differential evolution is applied to solve the fuzzy goal attainment problem to obtain a global Pareto solution. [Copyright &y& Elsevier]