辽宁石油化工大学学报

辽宁石油化工大学学报 ›› 2016, Vol. 36 ›› Issue (2): 52-59.DOI: 10.3696/j.issn.1672-6952.2016.02.014

• 计算机与自动化 • 上一篇    下一篇

基于改进NSGA-Ⅱ算法的氯乙烯精馏过程多目标优化

周 怡,苏成利   

  1. (辽宁石油化工大学信息与控制工程学院,辽宁抚顺113001)
  • 收稿日期:2016-01-15 修回日期:2016-02-16 出版日期:2016-04-25 发布日期:2016-05-06
  • 通讯作者: 苏成利(1977-),男,博士,教授,从事工业过程流程模拟、遗传算法多目标优化研究;E-mail:suchengli@lnpu.edu.cn。
  • 作者简介:周怡(1991-),女,硕士研究生,从事工业过程流程模拟、遗传算法多目标优化、氯乙烯精馏技术研究;E-mail: 309495050@qq.com。
  • 基金资助:
    国家自然科学基金资助(61203021);辽宁省科技攻关项目(2011216011);辽宁省自然科学基金项目(2013020024);
    辽宁省高等学校杰出青年学者成长计划(LJQ2015061)。

Multi-Objective Optimization Based on the Improved NSGA-Ⅱ Zlgorithm for Vinyl Chloride Rectification Process

Zhou Yi, Su Chengli   

  1. School of Information and Control Engineering, Liaoning Shihua University, Fushun Liaoning 113001, China
  • Received:2016-01-15 Revised:2016-02-16 Published:2016-04-25 Online:2016-05-06

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摘要： 针对氯乙烯精馏过程中氯乙烯产品纯度低、能耗高的现状,研究了一种新的改进型非支配排序遗传
算法(ImprovedNon-dominatedSortingGeneticAlgorithm,NSGA-Ⅱ),用于解决氯乙烯精馏过程多目标优化问题。
首先建立了氯乙烯精馏的模拟流程,然后通过对高低沸塔中进料位置、回流比等主要影响因素进行灵敏度分析,在
考虑其机理模型及实际生产状况等多种约束条件的基础上,建立了以氯乙烯纯度和能耗为目标的多目标优化函数,
最后利用改进NSGA-Ⅱ对目标函数进行求解。实验结果表明,相比于NSGA-Ⅱ,该改进算法能得到分布更为均匀
的Pareto最优解集,为氯乙烯精馏过程中参数的选择提供了有力支撑。

关键词: 氯乙烯精馏, 流程模拟, 多目标优化, 非支配排序遗传算法

Abstract:

A new improved non-dominated sorting genetic algorithm (NSGA-II) is studied aiming at solving the low purity, high energy consumption problems existed in vinyl chloride rectification process. The method can be used to solve the multi-objective optimization problem of vinyl chloride rectification process. The multi-objective optimization function with the energy consumption and purity of vinyl chlorides based on considering the various constraints of the mechanism model and the actual production conditions were established through the sensitivity analysis for the main operating parameters such as the feeding position and reflux ratio of high and low boiling tower and so on. Finally, the objective function is solved by using the improved NSGA-II. Compared to the NSGA-II, the experimental results show that the improved algorithm can get more uniform distribution of Pareto optimal solution set, which provides a strong support for the selection of parameters in the process of vinyl chloride distillation.

Key words:

Vinyl chloride rectification, Process simulation, Multi-objective optimization, Non-dominated sorting genetic algorithm

引用本文

周 怡,苏成利. 基于改进NSGA-Ⅱ算法的氯乙烯精馏过程多目标优化[J]. 辽宁石油化工大学学报, 2016, 36(2): 52-59.

Zhou Yi, Su Chengli.

Multi-Objective Optimization Based on the Improved NSGA-Ⅱ Zlgorithm for Vinyl Chloride Rectification Process[J]. Journal of Liaoning Petrochemical University, 2016, 36(2): 52-59.

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