Optimization of xylene adsorption separation process based on multi-objective teaching-learning-based optimization algorithm

HU Rong; YANG Minglei; QIAN Feng

doi:10.11949/j.issn.0438-1157.20141473

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Optimization of xylene adsorption separation process based on multi-objective teaching-learning-based optimization algorithm

更新时间：2025-12-10

- Optimization of xylene adsorption separation process based on multi-objective teaching-learning-based optimization algorithm
- CIESC Journal Issue 1, Pages: 326-332(2015)
- 作者机构：
  
  华东理工大学化工过程先进控制和优化技术教育部重点实验室,上海,200237
- 作者简介：
- 基金信息：
- DOI：10.11949/j.issn.0438-1157.20141473
  CLC： Q028
- Online First：05 January 2015，
  
  Published：05 January 2015
- 稿件说明：
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HU Rong, YANG Minglei, QIAN Feng. Optimization of xylene adsorption separation process based on multi-objective teaching-learning-based optimization algorithm[J]. CIESC Journal, 2015, (1): 326-332.
DOI：

HU Rong, YANG Minglei, QIAN Feng. Optimization of xylene adsorption separation process based on multi-objective teaching-learning-based optimization algorithm[J]. CIESC Journal, 2015, (1): 326-332. DOI： 10.11949/j.issn.0438-1157.20141473.

摘要

以C8芳烃混合物的吸附分离过程作为研究对象

应用多目标教学优化算法(multi-objective teaching-learning-based optimization algorithm

MOTLBO)对模拟移动床多目标优化问题进行求解。采用TMB方法

建立了模拟移动床模型

并对两个典型的模拟移动床多目标操作优化问题进行了优化设计。通过与NSGA-Ⅱ算法的比较

证明了多目标教学优化算法在求解模拟移动床多目标优化问题上的有效性和优势。此外

还分析了抽出液流量、抽余液流量以及步进时间等对多目标优化非劣解的影响

优化结果为模拟移动床分离过程的工艺设计和操作提供了依据。

Abstract

Multi-objective teaching-learning-base optimization (MOTLBO) algorithm has been employed to investigate the multi-objective optimization problem of simulated moving bed chromatography separation for the recovery of p-xylene from a mixture of C8 aromatics. The separation process was simulated using true moving bed (TMB) modeling strategy. Based on the MOTLBO algorithm

the optimal operation conditions are designed for two typical multi-objective optimization problems. Comparing with NSGA-Ⅱ

the MOTLBO algorithm has been verified to be more efficient in solving the multi-objective optimization problem of simulated moving bed. In addition

The influences of the extract flow rate

the raffinate flow rate and the switching time on the pareto optimal solutions were also analyzed. The optimization can facilitate the design and operation of simulated moving bed.

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