A review of optimization rectification systems based on multi-objective

被引：0

作者：

Zhang S. ^{[1
]}

Gao W. ^{[1
]}

Qi M. ^{[1
]}

Yu W. ^{[1
]}

Wang H. ^{[1
]}

机构：

[1] School of Chemical Engineering, Hebei University of Technology, Tianjin

来源：

Huagong Jinzhan/Chemical Industry and Engineering Progress | 2019年 / 38卷 / S1期

关键词：

distillation system; genetic algorithm; multi-objective; neural networks; optimization; orthogonal design; particle swarm; response surface;

D O I：

10.16085/j.issn.1000-6613.2019-0608

中图分类号：

学科分类号：

摘要：

Distillation system is studied in the multi-objective optimization of multiple parameter analysis, analysis of lists of artificial neural network, the orthogonal design, the response surface, genetic algorithm and particle swarm algorithm in distillation system, the application of multi-objective optimization, to summarizes the optimization algorithm of the distillation system and seek the solution to the optimal operating conditions, provide reference for rectifying column of multi-objective optimization. The results show that these algorithms can be used in the actual distillation system, aiming at the complex, variable and mixed programming problems of the current distillation system, the distillation system can be well modeled and predicted. It can be used to solve the optimal operation conditions in the distillation process, reduce the irreversibility of the system, realize the energy saving optimization of the distillation system, improve the product quality and reduce the energy consumption. It is proved that the method of multi-objective optimization distillation system is feasible, and that the method of multi-step optimization distillation system is feasible by combining multiple optimization algorithms in practical production. © 2019, Chemical Industry Press Co., Ltd.. All rights reserved.

引用

页码：1 / 9

页数：8

共 39 条

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