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A novel 3-layer mixed cultural evolutionary optimization framework for optimal operation of syngas production in a Texaco coal-water slurry gasifier
Cao, Cuiwen1; Zhang, Yakun1; Yu, Teng1; Gu, Xingsheng1; Xin, Zhong2; Li, Jie3
2015-09-01
Source PublicationCHINESE JOURNAL OF CHEMICAL ENGINEERING
ISSN1004-9541
Volume23Issue:9Pages:1484-1501
AbstractOptimizing operational parameters for syngas production of Texaco coal-water slurry gasifier studied in this paper is a complicated nonlinear constrained problem concerning 3 BP (Error Back Propagation) neural networks. To solve this model, a new 3-layer cultural evolving algorithm framework which has a population space, a medium space and a belief space is firstly conceived. Standard differential evolution algorithm (DE), genetic algorithm (GA), and particle swarm optimization algorithm (PSO) are embedded in this framework to build 3-layer mixed cultural DE/GA/PSO (3LM-CDE, 3LM-CGA, and 3LM-CPSO) algorithms. The accuracy and efficiency of the proposed hybrid algorithms are firstly tested in 20 benchmark nonlinear constrained functions. Then, the operational optimization model for syngas production in a Texaco coal-water slurry gasifier of a real-world chemical plant is solved effectively. The simulation results are encouraging that the 3-layer cultural algorithm evolving framework suggests ways in which the performance of DE, GA, PSO and other population-based evolutionary algorithms (EAs) can be improved, and the optimal operational parameters based on 3LM-CDE algorithm of the syngas production in the Texaco coal-water slurry gasifier shows outstanding computing results than actual industry use and other algorithms. (C) 2015 The Chemical Industry and Engineering Society of China, and Chemical Industry Press. All rights reserved.
Keyword3-layer Mixed Cultural Evolutionary Framework Optimal Operation Syngas Production Coal-water Slurry Gasifier
SubtypeArticle
WOS HeadingsScience & Technology ; Technology
DOI10.1016/j.cjche.2015.03.005
Indexed BySCI
Language英语
WOS KeywordCONSTRAINED OPTIMIZATION ; DIFFERENTIAL EVOLUTION ; GENETIC ALGORITHM ; PARTIAL OXIDATION ; SYNTHESIS GAS ; GASIFICATION ; INTEGRATION ; BIOMASS ; DESIGN ; MODEL
WOS Research AreaEngineering
WOS SubjectEngineering, Chemical
Funding OrganizationNational Natural Science Foundation of China(61174040 ; Shanghai Commission of Nature Science(12ZR1408100) ; U1162110 ; 21206174)
WOS IDWOS:000363791000009
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ipe.ac.cn/handle/122111/19757
Collection多相复杂系统国家重点实验室
Affiliation1.E China Univ Sci & Technol, Minist Educ, Key Lab Adv Control & Optimizat Chem Proc, Shanghai 200237, Peoples R China
2.E China Univ Sci & Technol, State Key Lab Chem Engn, Shanghai 200237, Peoples R China
3.Chinese Acad Sci, Inst Proc Engn, State Key Lab Multiphase Complex Syst, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Cao, Cuiwen,Zhang, Yakun,Yu, Teng,et al. A novel 3-layer mixed cultural evolutionary optimization framework for optimal operation of syngas production in a Texaco coal-water slurry gasifier[J]. CHINESE JOURNAL OF CHEMICAL ENGINEERING,2015,23(9):1484-1501.
APA Cao, Cuiwen,Zhang, Yakun,Yu, Teng,Gu, Xingsheng,Xin, Zhong,&Li, Jie.(2015).A novel 3-layer mixed cultural evolutionary optimization framework for optimal operation of syngas production in a Texaco coal-water slurry gasifier.CHINESE JOURNAL OF CHEMICAL ENGINEERING,23(9),1484-1501.
MLA Cao, Cuiwen,et al."A novel 3-layer mixed cultural evolutionary optimization framework for optimal operation of syngas production in a Texaco coal-water slurry gasifier".CHINESE JOURNAL OF CHEMICAL ENGINEERING 23.9(2015):1484-1501.
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