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首页> 外文期刊>Biotechnology Progress >Global Optimization of the Saccharomyces cerevisiae: Fermentation Process
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Global Optimization of the Saccharomyces cerevisiae: Fermentation Process

机译:酿酒酵母的全球优化:发酵过程。

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In this article, steady-state optimization of the Saccharomyces cerevisiae fermentation process problem is performed revealing the existence of multiple optimum solutions. The globally optimum solution was determined using the NEOS global optimization solver LINDO. A branch and bound strategy (bnb20.m) and the global search and multistart algorithms in the MATLAB global optimization toolbox were successful in determining locally optimum solutions and these results are validated by plotting the objective function against the decision variables. While in some cases all the strategies were successful in obtaining the globally optimum solutions, an example is presented where the most beneficial product value, which is not a stationary point and lies on the feasible boundary, is obtained by the UNDO global optimization solver (but not the other routines) as the globally optimum solution. The Jones-Kompala model was used to model the steady-state of the fermentation process. While several articles have been published demonstrating the existence of nonlinearities and bifurcations in this model, the challenges posed by this model to optimization has never been investigated so far and this work attempts to do so. Both dilution rate and the oxygen mass transfer coefficient were used as the decision variables individually and together.
机译:在本文中,对啤酒酵母发酵过程问题进行了稳态优化,揭示了多个最优解的存在。使用NEOS全局优化求解器LINDO确定了全局最优解。 MATLAB全局优化工具箱中的分支定界策略(bnb20.m)以及全局搜索和多启动算法已成功确定了局部最优解,并且通过将目标函数与决策变量作图来验证了这些结果。尽管在某些情况下所有策略都成功获得了全局最优解,但还是给出了一个示例,其中由UNDO全局优化求解器获得了最有益的产品价值,该价值不是固定点,而是位于可行边界上(但而不是其他例程)作为全局最优解。 Jones-Kompala模型用于模拟发酵过程的稳态。尽管已经发表了几篇文章来证明此模型中存在非线性和分叉,但迄今为止,尚未对该模型对优化提出的挑战进行过研究,并且本工作试图做到这一点。稀释率和氧气传质系数都单独或一起用作决策变量。

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