换热网络多目标综合优化算法研究进展

doi:10.16085/j.issn.1000-6613.2016.02.002

化工进展 ›› 2016, Vol. 35 ›› Issue (02): 352-357.DOI: 10.16085/j.issn.1000-6613.2016.02.002

换热网络多目标综合优化算法研究进展

吕俊锋, 肖武, 王开锋, 李中华, 贺高红

大连理工大学精细化工国家重点实验室, 膜科学与技术研究开发中心, 辽宁大连 116024

收稿日期:2015-09-01 修回日期:2015-09-10 出版日期:2016-02-05 发布日期:2016-02-05
通讯作者: 肖武,副教授,硕士生导师,主要从事化工系统工程和过程强化的研究。E-mail:wuxiao@dlut.edu.cn。
作者简介:第一作者:吕俊锋(1992-),男,硕士研究生,主要从事过程系统优化研究。
基金资助:
国家自然科学基金(21206014,21125628)、中央高校基本科研业务费专项基金(DUT14LAB14)及中国石油化工股份有限公司资助项目(X514001)。

Research progress on optimization algorithms in multi-objective synthesis of heat exchanger networks

LÜ Junfeng, XIAO Wu, WANG Kaifeng, LI Zhonghua, HE Gaohong

State Key Laboratory of Fine Chemicals, R&D Center of Membrane Science and Technology, Dalian University of Technology, Dalian 116024, Liaoning, China

Received:2015-09-01 Revised:2015-09-10 Online:2016-02-05 Published:2016-02-05

摘要/Abstract

摘要： 资源和能源的可持续发展使得换热网络综合不仅要考虑经济性,同时要满足柔性、可靠性、可操作性和环境影响度等指标的要求。目前,换热网络多目标综合的研究有了初步进展并引起了广泛关注。本文阐述了进行换热网络多目标综合的必要性并总结了相关研究。重点对常用的多目标优化算法作了总结和对比,综述了其在换热网络多目标优化设计中的应用进展。研究表明,传统多目标算法越来越无法满足复杂模型的求解,而多目标进化算法可以很好地求解换热网络综合多目标优化问题,其中NSGA-Ⅱ算法是目前应用最广的有效算法。提出尝试NSGA-Ⅱ等多目标进化算法,基于超结构建立包括经济性、柔性、可靠性、可操作性和环境影响度等在内的换热网络多目标综合模型,给出Pareto最优解集合供决策者选择是未来的研究方向。

关键词: 系统工程, 优化设计, 换热网络, 多目标, 算法, NSGA-Ⅱ

Abstract: For the sustainable development in resources and energy,the designers should not only consider economy,but also flexibility,reliability,operability and environmental impact in the synthesis of heat exchanger networks(HENs). Multi-objective synthesis of HENs has got preliminary progress and drawn great attention. This paper illustrates the necessity of multi-objective synthesis of HENs and summarizes the research progress on multi-objective synthesis of HENs. The summary and comparison of the algorithms for solving multi-objective optimization problems were mainly focused. Application in multi-objective synthesis of HENs was reviewed. Research shows that traditional multi-objective algorithms are less suitable for solving the problems of complex superstructure. However,multi-objective evolutionary algorithms can solve multi-objective problems better in the synthesis of HENs. Non-dominated sorting genetic algorithm(NSGA-Ⅱ) is one of the most popular and effective applied algorithms. It was proposed that based on superstructure,establishing multi-objective models which involve economy,flexibility,reliability,operability and environmental impact and then present the decision makers with Pareto optimum solutions is the future of HEN synthesis.

Key words: systems engineering, optimal design, HENs, multi-objective, algorithms, NSGA-Ⅱ

中图分类号:

TQ021.8

吕俊锋, 肖武, 王开锋, 李中华, 贺高红. 换热网络多目标综合优化算法研究进展[J]. 化工进展, 2016, 35(02): 352-357.

LÜ Junfeng, XIAO Wu, WANG Kaifeng, LI Zhonghua, HE Gaohong. Research progress on optimization algorithms in multi-objective synthesis of heat exchanger networks[J]. Chemical Industry and Engineering Progree, 2016, 35(02): 352-357.

参考文献

[1] 霍兆义,尹洪超,赵亮,等. 国内换热网络综合方法研究进展与展望[J]. 化工进展,2012,31(4):726-731.
[2] KANG L,LIU Y,LIANG X. Multi-objective optimization of heat exchanger networks based on analysis of minimum temperature difference and accumulated CO₂ emissions[J]. Applied Thermal Engineering,2015,87(5):736-748.
[3] RAVAGNANI M A S S,MANO T B,CARVALHO E P,et al. Multi-objective heat exchanger networks synthesis considering economic and environmental optimization[J]. Computer Aided Chemical Engineering,2014,33:1579-1584.
[4] YI D K,HAN Z Z,WANG K F,et al. Strategy for synthesis of flexible heat exchanger networks embedded with system reliability analysis[J]. Chinese Journal of Chemical Engineering,2013,21(7):742-753.
[5] ESCOBAR M,TRIERWEILER J O,GROSSMANN I E. Simultaneous synthesis of heat exchanger networks with operability considerations:flexibility and controllability[J]. Computers & Chemical Engineering,2013,55:158-180.
[6] WEN Y,SHONNARD D R. Environmental and economic assessments of heat exchanger networks for optimum minimum approach temperature[J]. Computers & Chemical Engineering,2003,27(11):1577-1590.
[7] CHEN C L,HUNG P S. Multicriteria synthesis of flexible heat-exchanger networks with uncertain source-stream temperatures [J]. Chemical Engineering and Processing:Process Intensification,2005,44(1):89-100.
[8] BJÖRK K M,WESTERLUND T. Proceedings of the IEASTED international conference:Modelling,identification,and control[C]// Acta Press,Calgary,AB,Canada,2002.
[9] SREEPATHI B K,RANGAIAH G P. Review of heat exchanger network retrofitting methodologies and their applications[J]. Industrial & Engineering Chemistry Research,2014,53(28):11205-11220.
[10] COELLO C A. Evolutionary multi-objective optimization:a historical view of the field[J]. Computational Intelligence Magazine,IEEE,2006,1(1):28-36.
[11] NA J,JUNG J,PARK C,et al. Simultaneous synthesis of a heat exchanger network with multiple utilities using utility substages[J]. Computers & Chemical Engineering,2015,79:70-79.
[12] ZHOU A,QU B Y,LI H,et al. Multiobjective evolutionary algorithms:a survey of the state of the art[J]. Swarm and Evolutionary Computation,2011,1(1):32-49.
[13] LÓPEZ-MALDONADO L A,PONCE-ORTEGA J M,SEGOVIA-HERNÁNDEZ J G. Multiobjective synthesis of heat exchanger networks minimizing the total annual cost and the environmental impact[J]. Applied Thermal Engineering,2011,31(6):1099-1113.
[14] KLEMEŠ J J,KRAVANJA Z. Forty years of heat integration:pinch analysis and mathematical programming[J]. Current Opinion in Chemical Engineering,2013,2(4):461-474.
[15] 温录亮. 多目标最优化方法与应用[D]. 广州:暨南大学,2009.
[16] JIN Z L,CHEN X T,WANG Y Q,et al. Heat exchanger network synthesis based on environmental impact minimization[J]. Clean Technologies and Environmental Policy,2014,16(1):183-187.
[17] KIRLIK G,SAYIN S. A new algorithm for generating all nondominated solutions of multiobjective discrete optimization problems[J]. European Journal of Operational Research,2014,232(3):479-488.
[18] VASKAN P,GUILLÉN-GOSÁLBEZ G,JIMÉNEZ L. Multi- objective design of heat-exchanger networks considering several life cycle impacts using a rigorous MILP-based dimensionality reduction technique[J]. Applied Energy,2012,98:149-161.
[19] MIETTINEN K,MÄKELÄ M M. Interactive multiobjective optimization system WWW-NIMBUS on the internet[J]. Computers & Operations Research,2000,27(7):709-723.
[20] LAUKKANEN T,TVEIT T M,OJALEHTO V,et al. An interactive multi-objective approach to heat exchanger network synthesis[J]. Computers & Chemical Engineering,2010,34(6):943-952.
[21] LAUKKANEN T,TVEIT T M,OJALEHTO V,et al. Bilevel heat exchanger network synthesis with an interactive multi-objective optimization method[J]. Applied Thermal Engineering,2012,48:301-316.
[22] DEB K,PRATAP A,AGARWAL S,et al. A fast and elitist multi-objective genetic algorithm:NSGA-Ⅱ[J]. IEEE Transactions on Evolutionary Computation,2002,6(2):182-197.
[23] METAXIOTIS K,LIAGKOURAS K. Multiobjective evolutionary algorithms for portfolio management:A comprehensive literature review[J]. Expert Systems with Applications,2012,39(14):11685-11698.
[24] 公茂果,焦李成,杨咚咚,等. 进化多目标优化算法研究[J]. 软件学报,2009,20(2):271-289.
[25] AGARWAL A,GUPTA S K. Multiobjective optimal design of heat exchanger networks using new adaptations of the elitist. nondominated sorting genetic algorithm,NSGA-Ⅱ[J]. Industrial & Engineering Chemistry Research,2008,47(10):3489-3501.
[26] 任建强. 管壳式换热器及换热器网络的多目标优化设计[D]. 济南:山东大学,2011.
[27] 林露. 基于非支配排序遗传算法的换热网络多目标优化[D]. 杭州:浙江工业大学,2013.
[28] SRINIVASAN S,RAMAKRISHNAN S. Evolutionary multi objective optimization for rule mining:a review[J]. Artificial Intelligence Review,2011,36(3):205-248.
[29] 高媛. 非支配排序遗传算法 (NSGA) 的研究与应用[D]. 杭州:浙江大学,2006.
[30] VON LÜCKEN C,BARÁN B,BRIZUELA C. A survey on multi-objective evolutionary algorithms for many-objective problems[J]. Computational Optimization and Applications,2014,58(3):707-756.
[31] 师瑞峰. 多目标进化算法研究及其在生产排序中的应用[D]. 北京:北京航空航天大学,2006.
[32] 马小姝,李宇龙,严浪. 传统多目标优化方法和多目标遗传算法的比较综述[J]. 电气传动自动化,2010,32(3):48-50.

换热网络多目标综合优化算法研究进展

Research progress on optimization algorithms in multi-objective synthesis of heat exchanger networks

PDF (PC)

可视化

被引次数

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价

[1]	杨建平. 降低HPPO装置反应系统原料消耗的PSE[J]. 化工进展, 2023, 42(S1): 21-32.
[2]	陈匡胤, 李蕊兰, 童杨, 沈建华. 质子交换膜燃料电池气体扩散层结构与设计研究进展[J]. 化工进展, 2023, 42(S1): 246-259.
[3]	孙玉玉, 蔡鑫磊, 汤吉海, 黄晶晶, 黄益平, 刘杰. 反应精馏合成甲基丙烯酸甲酯工艺优化及节能[J]. 化工进展, 2023, 42(S1): 56-63.
[4]	张凤岐, 崔成东, 鲍学伟, 朱炜玄, 董宏光. 胺液吸收-分步解吸脱硫工艺的设计与评价[J]. 化工进展, 2023, 42(S1): 518-528.
[5]	刘炫麟, 王驿凯, 戴苏洲, 殷勇高. 热泵中氨基甲酸铵分解反应特性及反应器结构优化[J]. 化工进展, 2023, 42(9): 4522-4530.
[6]	张帆, 陶少辉, 陈玉石, 项曙光. 基于改进恒热传输模型的精馏模拟初始化[J]. 化工进展, 2023, 42(9): 4550-4558.
[7]	王晨, 白浩良, 康雪. 大功率UV-LED散热与纳米TiO₂光催化酸性红26耦合系统性能[J]. 化工进展, 2023, 42(9): 4905-4916.
[8]	李蓝宇, 黄新烨, 王笑楠, 邱彤. 化工科研范式智能化转型的思考与展望[J]. 化工进展, 2023, 42(7): 3325-3330.
[9]	林海, 王彧斐. 考虑噪声约束的分布式风场布局优化[J]. 化工进展, 2023, 42(7): 3394-3403.
[10]	王俊杰, 潘艳秋, 牛亚宾, 俞路. 分子水平催化重整装置模型构建及应用[J]. 化工进展, 2023, 42(7): 3404-3412.
[11]	周龙大, 赵立新, 徐保蕊, 张爽, 刘琳. 电场-旋流耦合强化多相介质分离研究进展[J]. 化工进展, 2023, 42(7): 3443-3456.
[12]	薛凯, 王帅, 马金鹏, 胡晓阳, 种道彤, 王进仕, 严俊杰. 工业园区分布式综合能源系统的规划与调度[J]. 化工进展, 2023, 42(7): 3510-3519.
[13]	顾诗亚, 董亚超, 刘琳琳, 张磊, 庄钰, 都健. 考虑中间节点的碳捕集管路系统设计与优化[J]. 化工进展, 2023, 42(6): 2799-2808.
[14]	凌山, 刘聚明, 张前程, 李艳. 模拟移动床分离过程及其优化方法研究进展[J]. 化工进展, 2023, 42(5): 2233-2244.
[15]	李雪, 王艳君, 王玉超, 陶胜洋. 仿生表面用于雾水收集的最新研究进展[J]. 化工进展, 2023, 42(5): 2486-2503.