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A Modified Differential Evolution Algorithm for Feed Rate Optimization of Fed-batch Fermentation

机译：一种改进的差分演化算法，用于饲料批量发酵的饲料速率优化

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摘要

A novel modified differential evolution (MDE) algorithm that contains simplex acceleration operator and chaotic migration operator is proposed for feed rate optimization of fed-batch fermentation process. The simplex acceleration operator improves the speed of getting global optimum, and the chaotic migration operator keeps the individuals' diversity in the population to overcome prematurity. Three selection rules are introduced into the algorithm for constrained optimization problem, which ensures that the solution could accord with the constraint condition. The modified algorithm is applied to optimize feed rate of a certain fed-batch fermentation process, which improves the final product yield. The results show that the algorithm is effective.
机译：提出了一种新的改进的差分演进（MDE）算法，其包含单纯x加速度运算符和混沌迁移操作员，用于FED批量发酵过程的进料速率优化。 Simplex加速度运营商提高了全球最佳的速度，混乱的迁移运营商将个人的多样性保持在人口中以克服早产。将三个选择规则引入到约束优化问题的算法中，这确保了解决方案可以符合约束条件。应用修饰的算法优化某种FED分批发酵过程的进料速率，从而提高了最终产品产率。结果表明该算法是有效的。

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