多目标遗传算法在反应精馏优化中的应用

反应精馏是反应与精馏的复合过程，因其具有选择性强、投资少、能耗低等优点而受到研究者们的广泛关注，并且在工业生产中得到广泛的应用。利用人工神经网络（ANN）模型来模拟反应精馏过程。在建立ANN模型时，首先用ASPEN软件模拟计算出多组数据以弥补实验数据不多的不足，并在此基础上用多目标遗传算法（GA）进行操作条件的优化。优化结果表明，多目标遗传算法结合ANN对反应精馏进行优化是可行的，而且具有很高的精度。以合成乙酸乙酯的反应精馏过程为例说明上述模拟和优化方法。

Application of Multi-Objective Genetic Algorithm in the Optimization of Reactive Distillation

Reactive distillation is a process combining chemical reaction with distillation separation. It has attracted many researchers and has been used widely for the virtues of high selectivity, low capital investment and little energy consumption. In this article, artificial neural network （ANN） model was presented to simulate reactive distillation. A lot of data were produced by ASPEN to make up the shortage of experimental data when setting up the ANN models. In company with the ANN models, the multi-objective genetic algorithm was used to optimize the process of reactive distillation. Results show that the proposed method is feasible and has high precision. Reactive distillation for synthesizing ethyl acetate was taken as an example to demonstrate the proposed simulation and optimization methods.