化工进展 ›› 2016, Vol. 35 ›› Issue (10): 3092-3100.DOI: 10.16085/j.issn.1000-6613.2016.10.012

• 化工过程与装备 • 上一篇    下一篇

一种新型Powell粒子群算法同步综合换热网络

张春伟, 崔国民   

  1. 上海理工大学新能源科学与工程研究所, 上海 200093
  • 收稿日期:2016-01-27 修回日期:2016-02-23 出版日期:2016-10-05 发布日期:2016-10-05
  • 通讯作者: 崔国民,教授,博士生导师。E-mail:cgm1226@163.com
  • 作者简介:张春伟(1992-),男,硕士研究生,从事过程系统优化研究。
  • 基金资助:
    国家自然科学基金项目(51176125)。

A novel Powell particle swarm optimization algorithm for simultaneous synthesis of heat exchanger networks

ZHANG Chunwei, CUI Guomin   

  1. Research Institute of New Energy Science and Technology, University of Shanghai for Science and Technology, Shanghai 200093, China
  • Received:2016-01-27 Revised:2016-02-23 Online:2016-10-05 Published:2016-10-05

摘要: 针对换热网络同步综合方法的不足,本文提出了一种新型Powell粒子群算法,具有传统确定性方法的高精度以及启发式方法的高效率。同时针对群体智能算法优化换热网络问题时存在的不足,提出了云记忆体和个体对立策略,有效地避免算法发生早熟现象,扩大搜索范围。为处理整型变量而提出的两条整型变量优化策略与Powell粒子群算法结合,实现了连续变量与整型变量的同步优化。最后,选取两个经典算例验证算法的性能,均获得了优于文献的结果,表明算法能够找到更优的换热网络结构,是一种处理混合整数非线性问题的有效方法。

关键词: 换热网络综合, 整型变量优化, Powell法, 群体智能

Abstract: Due to the defect of simultaneous methods for heat exchanger networks synthesis,a novel Powell particle swarm optimization(PPSO) algorithm was proposed,which has both high precision of the deterministic methods and high efficiency of the stochastic algorithms. For overcoming disadvantages of stochastic algorithms,the cloud memory and the opposite strategy of individualswere proposed,which can avoid premature convergence and expand the search space. In addition,two optimizing strategies of integer variables were combined with PPSO algorithm in order to simultaneously optimize continuous and integer variables. The presented approach was tested on two typical benchmark problems. The obtained solutions are better than that published in the literature. Results showed that the presented algorithm can find better designs,which is conductive to cost saving in industrial production.

Key words: heat exchanger networks synthesis, integer variables, Powell method, swarm intelligence

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