A structure evolution strategy motivated by large step size for optimization of heat exchanger network

SUN Tao; CUI Guomin; CHEN Jiaxing

doi:10.11949/j.issn.0438-1157.20171625

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A structure evolution strategy motivated by large step size for optimization of heat exchanger network

更新时间：2025-12-10

- A structure evolution strategy motivated by large step size for optimization of heat exchanger network
- CIESC Journal Issue 7, Pages: 3135-3148(2018)
- 作者机构：
  
  上海理工大学新能源科学与工程研究所,上海,200093
- 作者简介：
- 基金信息：
- DOI：10.11949/j.issn.0438-1157.20171625
  CLC： K124
- Online First：05 July 2018，
  
  Published：05 July 2018
- 稿件说明：
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SUN Tao, CUI Guomin, CHEN Jiaxing. A structure evolution strategy motivated by large step size for optimization of heat exchanger network[J]. CIESC Journal, 2018, (7): 3135-3148.
DOI：

SUN Tao, CUI Guomin, CHEN Jiaxing. A structure evolution strategy motivated by large step size for optimization of heat exchanger network[J]. CIESC Journal, 2018, (7): 3135-3148. DOI： 10.11949/j.issn.0438-1157.20171625.

摘要

强制进化随机游走算法（random walk algorithm with compulsive evolution，RWCE）具有进化策略简单、控制参数少、全局搜索能力强等特点，是换热网络优化的一种有效方法。鉴于步长对RWCE算法跳出局部最优解有重要的影响，针对RWCE算法的步长分布进行研究，通过分析大步长在局部极值跳出中的作用机理，建立了一种全新的步长组合生成方法，并据此提出了一种大步长激励的结构进化策略。最后，通过3个算例验证了结构进化策略的有效性，与文献结果进行对比，结果表明大步长激励的结构进化策略提高了算法的全局搜索能力。

Abstract

Random walk algorithm with compulsive evolution (RWCE) was an effective method for the optimization of heat exchanger network with the advantage of simple evolutionary strategy and less control parameters. The RWCE algorithm had the capacity to jump out of the local optimal through continuously accepting the imperfect solutions

but its jumping efficiency was often limited by the step size. The global search ability of the algorithm was reduced. Therefore

a novel combined step size generation method was established by studying the step size distribution of RWCE algorithm and analyzing the mechanism of large step size assisted to jump out of local optimal

then a structure evolution strategy motivated by large step size was proposed. Finally

the validity of the proposed structure evolution strategy was verified by three cases. Compared with the literature results

the results showed that the structure evolution strategy motivated by large step size had a strong global search ability.

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