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A Multiple-objective Optimization of Whey Fermentation in Stirred Tank Bioreactors

机译:搅拌罐生物反应器中乳清发酵的多目标优化

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A multiple-objective optimization is applied to find an optimal policy of a fed-batch fermentation process for lactose oxidation from a natural substratum of the strain Kluyveromyces marxianus var. lactis MC5. The optimal policy is consisted of feed flow rate, agitation speed, and gas flow rate. The multiple-objective problem includes: the total price of the biomass production, the second objective functions are the separation cost in downstream processing and the third objective function corresponds to the oxygen mass-transfer in the bioreactor. The multiple-objective optimization are transforming to standard problem for optimization with single-objective function. Local criteria are defined utility function with different weight for single-type vector task. A fuzzy sets method is applied to be solved the maximizing decision problem. A simple combined algorithm guideline to find a satisfactory solution to the general multiple-objective optimization problem. The obtained optimal control results have shown an increase of the process productiveness and a decrease of the residual substrate concentration
机译:应用多目标优化,从马克斯克鲁维酵母变种的天然基质中找到用于乳糖氧化的分批补料发酵过程的最佳策略。乳酸MC5。最佳策略包括进料流速,搅拌速度和气体流速。多目标问题包括:生物质生产的总价格,第二目标函数是下游处理中的分离成本,第三目标函数对应于生物反应器中的氧气传质。多目标优化正在转化为标准问题,以实现具有单目标功能的优化。本地标准是针对单类型矢量任务定义的具有不同权重的效用函数。应用模糊集方法求解最大化决策问题。一个简单的组合算法指南,可为一般的多目标优化问题找到满意的解决方案。获得的最佳控制结果显示出过程生产率的提高和残留底物浓度的降低

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