基于改进自适应遗传算法的动力学模型优化

Optimizing of the Kinetic Models Based on Modified Adaptive Genetic Algorithm

研究丁二酸是现代工业生物技术中一种重要的生物基产品。生物发酵法生产丁二酸具有高效率、环保性和原料的可持续利用性而受到众多科学家的推崇。建立相对完善的丁二酸发酵动力学模型,既可以帮助研究人员适当减少繁琐的实验工作,又有助于实现对发酵过程培养条件的优化与控制,辅助提高工艺水平。通过对遗传算法的进一步研究,改进了交叉与变异遗传算子,并引入精英保留策略,提出了改进的自适应遗传算法。结果表明,用改进自适应遗传算法优化丁二酸发酵动力学模型参数,在有效解决标准遗传算法收敛速度慢及局部搜索能力不强等问题的同时,能够获得相对完善的丁二酸发酵动力学模型。

Succinic acid is a representative and significant bio - based product in the modem industrial biologic technology. The bioconversion of succinic acid is propitious to the protection of the environment and the continuable utilization of the resources. In order to reduce the burden of the experiment and improve the fermentation technology properly, the kinetic model for the fermentation process of succinic acid was established. Based on the further research of genetic algorithm, the operation of crossover and mutation were modified and the strategy of elitist selection was adopted. The modified adaptive genetic algorithm showed its better local optimal ability and its faster convergence ability than standard genetic algorithm. The results indicated that the application of the modified adaptive genetic algorithm in the optimization of the kinetic parameters was effective and the kinetic model for the fermentation process of succinic acid was obtained.