A novel 3-layer mixed cultural evolutionary optimization framework for optimal operation of syngas production in a Texaco coal-water slurry gasifier
文献类型：期刊论文
| 作者 | Cao, Cuiwen1; Zhang, Yakun1; Yu, Teng1; Gu, Xingsheng1; Xin, Zhong2; Li, Jie3 |
| 刊名 | CHINESE JOURNAL OF CHEMICAL ENGINEERING
 |
| 出版日期 | 2015-09-01 |
| 卷号 | 23期号:9页码:1484-1501 |
| 关键词 | 3-Layer mixed cultural evolutionary framework Optimal operation Syngas production Coal-water slurry gasifier |
| ISSN号 | 1004-9541 |
| 英文摘要 | Optimizing 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. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Engineering, Chemical |
| 研究领域[WOS] | Engineering |
| 关键词[WOS] | CONSTRAINED OPTIMIZATION ; DIFFERENTIAL EVOLUTION ; GENETIC ALGORITHM ; PARTIAL OXIDATION ; SYNTHESIS GAS ; GASIFICATION ; INTEGRATION ; BIOMASS ; DESIGN ; MODEL |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000363791000009 |
| 源URL | [http://ir.ipe.ac.cn/handle/122111/19757]  |
| 专题 | 过程工程研究所_多相复杂系统国家重点实验室 |
| 作者单位 | 1.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 |
| 推荐引用方式 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. |
入库方式： OAI收割
来源：过程工程研究所
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