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Application of Genetic Algorithm to Determine Kinetic Parameters of Free Radical Polymerization of Vinyl Acetate by Multi-objective Optimization Technique

机译:遗传算法在多目标优化技术确定乙酸乙烯酯自由基聚合动力学参数中的应用

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摘要

A Multi-objective optimization procedure has been developed to determine some kinetic parameters of free radical polymerization of vinyl acetate based on genetic algorithm. For this purpose, mathematical modeling of free radical polymerization of vinyl acetate is carried out first and then selected kinetic parameters are optimized by minimizing objective functions defined from comparing experimental data and mathematical modeling outcomes. A ranking procedure is applied to classification of solutions, and a Pareto optimal set filter is used to preserve the non-dominated solutions on the basis of Pareto optimality definition. Results show by this optimization technique, kinetic parameters are calculated in reasonable time and computational costs near the global optimum without scalarization of objective functions into a single objective function.
机译:提出了一种基于遗传算法确定乙酸乙烯酯自由基聚合动力学参数的多目标优化程序。为此,首先进行乙酸乙烯酯自由基聚合的数学建模,然后通过最小化通过比较实验数据和数学建模结果定义的目标函数来优化选定的动力学参数。将排序过程应用于解决方案的分类,并使用帕累托最优集过滤器基于帕累托最优性定义来保留非主导解。结果表明,通过这种优化技术,可以在合理的时间内计算出动力学参数,并且在不将目标函数定标为单个目标函数的情况下,计算成本接近全局最优值。

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