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A Comparison of Variational and Genetic Algorithm Performances in the Optimization of a Polymerization Process

机译:变分和遗传算法的比较性能的优化聚合过程

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The aim of this work is to compare the performances of two well-known methods, Minimum Principle and Genetic Algorithm, in the optimization of the methyl methacrylate polymerization process in solution. In order to select a kinetic model for this process, the published kinetic models were reviewed and compared by simulation in similar operating conditions. Based on the kinetic model proposed by Baillagou and Soong (1985), the temperature profile necessary to attain, in a given reaction time, specified values for monomer conversion, number-average molecular weight and polydispersity index, was calculated. The temperature profiles calculated by the two optimization algorithms are practically identical, but they are obtained with different computational efforts. The results of this comparison are used to draw several conclusions regarding the proficiency of the two methods in the optimization of complex reaction processes.
机译:这项工作的目的是比较表演两个著名的方法,最少原理和遗传算法的甲基丙烯酸甲酯的优化聚合过程的解决方案。选择这一过程的动力学模型综述了动力学模型和出版相比模拟在类似的操作条件。Baillagou和宋子文(1985),温度配置文件必须达到,在一个给定的反应时间、单体转换指定的值相对分子量和多分散性指数计算。由两个温度资料计算优化算法几乎相同的,但是他们得到了不同的计算工作。比较得出几个结论关于这两种方法的熟练程度复杂的反应过程的优化。

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