具有步长调整策略的强制进化随机游走算法优化换热网络

doi:10.16085/j.issn.1000-6613.2017.02.006

化工进展 ›› 2017, Vol. 36 ›› Issue (02): 442-450.DOI: 10.16085/j.issn.1000-6613.2017.02.006

具有步长调整策略的强制进化随机游走算法优化换热网络

刘璞¹, 崔国民¹, 肖媛¹, 陈家星¹, 周剑卫²

1 上海理工大学新能源科学与工程研究所, 上海 200093;
2 哈尔滨哈锅锅炉工程技术公司, 黑龙江哈尔滨 150060

收稿日期:2016-06-17 修回日期:2016-09-17 出版日期:2017-02-05 发布日期:2017-02-05
通讯作者: 崔国民,教授,博士生导师,主要从事强化传热及高效换热器研究。E-mail:cgm1226@163.com。
作者简介:刘璞(1993-),男,硕士研究生,主要从事强化传热及过程系统优化研究。
基金资助:
上海市科委部分地方院校能力建设计划（16060502600）、国家自然科学基金（51176125）及沪江基金研究基地专项（D14001）项目。

Optimizing heat exchanger network by random walking algorithm with compulsive evolution combined with step length adjustment strategy

LIU Pu¹, CUI Guomin¹, XIAO Yuan¹, CHEN Jiaxing¹, ZHOU Jianwei²

1 Research Institute of New Energy Science and Technology, University of Shanghai for Science and Technology, Shanghai 200093, China;
2 Harbin Boiler Engineering Technology Company, Harbin 150060, Heilongjiang, China

Received:2016-06-17 Revised:2016-09-17 Online:2017-02-05 Published:2017-02-05

摘要/Abstract

摘要： 强制进化随机游走算法（random walking algorithm with compulsive evolution，RWCE）是一种优化换热网络的新方法，具有程序简单、算法适应性和全局搜索能力较强等优点。本文研究了最大步长对RWCE算法优化性能的影响，提出了抛物线函数的最大步长递减调整策略来平衡RWCE算法的全局搜索与局部搜索能力。将引入策略的RWCE算法与基础算法比较，发现加入最大步长递减调整策略的RWCE算法与基础RWCE算法相比，在进化后期能够跳出局部极小值，具有更强的局部搜索能力。采用10SP2、9SP和15SP换热网络实例检验加入此策略RWCE算法的有效性，其中10SP2和9SP算例的优化结果均好于文献最好结果，相比算例原始文献下降了20.98%和1.11%。对15SP算例优化找到了新的换热网络匹配结构，并好于多数无分流换热网络优化结果，且低于文献结果4.60%，证明了此方法在换热网络优化中具有较强的优化能力。

关键词: 强制进化随机游走算法, 换热网络优化, 全局搜索能力, 局部搜索能力

Abstract: Random walking algorithm with compulsive evolution(RWCE) is a novel heuristic method to optimize heat exchanger networks,which has a powerful global optimizing ability in the process of evolution. In this paper,the effect of maximal step length on the performance of RWCE algorithm was studied. To efficiently control the global and local search ability of the algorithm,a decreasing maximal step length adjustment strategy based on a parabola opening downwards curve was proposed. Compared with the basic algorithm,the strategy is capable of jumping out of local optima in the late evolution stage and strengthening the local search ability. The optimal results of three HEN cases (10SP2,9SP and 15SP) from literatures were used to test the effectiveness of the RWCE algorithm cooperated with proposed strategy. The results of former two(10SP2 and 9SP)are better than the best results published,which is 20.98% and 1.11% lower than the original literature results. A new heat exchanger networks structure was found in case 3(15SP),which is better than the majority of optimal results of no stream splits and 4.6% lower than the literature results. The results of these three cases demonstrate that the method enjoys a better optimization capability in the global optimization of heat exchanger network.

Key words: random walking algorithm with compulsive evolution(RWCE), heat exchanger network synthesis(HENS), global searching ability, local search capability

中图分类号:

TK124

刘璞, 崔国民, 肖媛, 陈家星, 周剑卫. 具有步长调整策略的强制进化随机游走算法优化换热网络[J]. 化工进展, 2017, 36(02): 442-450.

LIU Pu, CUI Guomin, XIAO Yuan, CHEN Jiaxing, ZHOU Jianwei. Optimizing heat exchanger network by random walking algorithm with compulsive evolution combined with step length adjustment strategy[J]. Chemical Industry and Engineering Progree, 2017, 36(02): 442-450.

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具有步长调整策略的强制进化随机游走算法优化换热网络

Optimizing heat exchanger network by random walking algorithm with compulsive evolution combined with step length adjustment strategy

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