计算物理 ›› 2021, Vol. 38 ›› Issue (1): 79-88.DOI: 10.19596/j.cnki.1001-246x.8182

• 研究论文 • 上一篇    下一篇

加权差分进化算法应用于换热网络综合

瞿悦呈1, 陈家星1,2, 崔国民1,2   

  1. 1. 上海理工大学能源与动力工程学院, 上海 200093;
    2. 上海市动力工程多相流动与传热重点实验室, 上海 200093
  • 收稿日期:2019-12-05 修回日期:2020-04-10 出版日期:2021-01-25 发布日期:2021-01-25
  • 通讯作者: 陈家星,E-mail:shaou26@163.com
  • 作者简介:瞿悦呈(1996-),男,上海人,本科生
  • 基金资助:
    国家自然科学基金(21978171)及上海市科委部分地方院校能力建设计划(16060502600)资助项目

Weighted Differential Evolution Algorithm for Heat Exchanger Network Synthesis

QU Yuecheng1, CHEN Jiaxing1,2, CUI Guomin1,2   

  1. 1. School of Energy and Power Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China;
    2. Shanghai Key Laboratory of Multiphase Flow and Heat Transfer in Power Engineering, Shanghai 200093, China
  • Received:2019-12-05 Revised:2020-04-10 Online:2021-01-25 Published:2021-01-25

摘要: 针对差分进化算法应用于换热网络受控制参数影响和后期种群多样性丧失进化乏力的不足,引入加权差分进化算法提升优化性能,算法的有效性已经在连续变量优化得到证明。本研究将其引入属于混合整型变量的换热网络综合,实现差分进化算法无控制参数调节。使用三个小到中等规模网络算例进行验证,其中两个算例取得目前公开文献最优年综合费用。通过建立等效缩放因子并考察其取值分布规律,探究加权差分进化算法的优化机理,为算法改进提供参考。

关键词: 加权差分进化算法, 换热网络, 多种群, 种群多样性, 缩放因子

Abstract: Considering that differential evolution algorithm (DE) is sensitive to the selection of control parameters and population diversity's decrease leads to the loss of power as DE is applied in heat exchanger network (HEN), a weighted differential evolution algorithm (WDE) is applied in this study. Effectiveness of the algorithm has been proved in continuous variable optimization. This study applies it in mixed integer nonlinear programming problems of HEN without controlling parameters. Three cases ranging from small to medium testify the effectiveness of WDE. By setting up equal mutation factor and analyzing its distribution, we explore WDE's optimization mechanism which provides reference for algorithm improvements.

Key words: weighted differential evolution, heat exchanger network, multi-population, population diversity, mutation factor

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