粒子群算法在化工过程优化中的应用

石油化工高等学校学报 ›› 2007, Vol. 20 ›› Issue (1): 90-93.

粒子群算法在化工过程优化中的应用

常晓萍1, 秦建华2, YigongLOU3

1.武汉工业学院电气信息工程系,湖北武汉430023;2.武汉化工学院化工系,湖北武汉430070;
3.CarnegieInstitutionofWashington,260PanamaStreet,Stanford,CA94305USA

收稿日期:2005-12-29 出版日期:2007-03-20 发布日期:2017-06-28
作者简介:常晓萍(1965-),女,湖北武汉市,实验师。
基金资助:
湖北省教育厅重点科研项目(2004D011)。

Application of Particle Swarm Algorithms to Optimization of Chemical Production Process

CHANG Xiao-ping 1, QIN Jian-hua2, Yigong LOU3 

1. Department of Electrical and Information Engineering, Wuhan Polytechnic University, Wuhan Hubei 430023, P.R.China；
2. Department of Chemical Engineering, Wuhan Institute of Chemical Technology, Wuhan Hubei, 430070, P.R.China；
3. Carnegie Institution of Washington，260 Panama Street,Stanford,CA94305 USA

Received:2005-12-29 Published:2007-03-20 Online:2017-06-28

摘要/Abstract

摘要： 对基本粒子群算法进行了智能化改进,并运用改进粒子群算法和MATLAB语言,对化工生产过程中的苯-甲苯闪蒸过程进行了优化仿真计算。仿真结果表明,在有效地调整温度、压力及分流系数的条件下,使得气相产物中苯的产量达到最大,实现了苯-甲苯闪蒸过程的最优化,同时也证明了粒子群算法可以有效地解决化工生产过程中的优化问题。

关键词: 苯-甲苯, 闪蒸过程, 粒子群算法, 优化仿真

Abstract: Basic particle swarm algorithms were intelligentized. Based on the intelligentized algorithms and MATLAB, simulation regarding optimization of benzene-toluene flash vaporization process during process of chemical production was made. The simulation result shows that the amount of benzene in vapor phase product reaches the maximum under the condition of effective adjustment of temperature, pressure and diffluence coefficient and the production process is optimized. It also proves that the intelligentized algorithms are practical in optimization of chemical production process.

Key words: Benzene-toluene, Flash vaporization process, Particle swarm algorithms, Optimization simulation

常晓萍, 秦建华, YigongLOU. 粒子群算法在化工过程优化中的应用[J]. 石油化工高等学校学报, 2007, 20(1): 90-93.

CHANG Xiao-ping,QIN Jian-hua, Yigong LOU. Application of Particle Swarm Algorithms to Optimization of Chemical Production Process[J]. Journal of Petrochemical Universities, 2007, 20(1): 90-93.

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