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Erschienen in:
2013 | OriginalPaper | Buchkapitel
Optimal Operation for 3 Control Parameters of Texaco Coal-Water Slurry Gasifier with MO-3LM-CDE Algorithms
verfasst von : Cuiwen Cao, Yakun Zhang, Xingsheng Gu
Erschienen in: Intelligent Computing for Sustainable Energy and Environment
Verlag: Springer Berlin Heidelberg
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Optimizing operation parameters for Texaco coal-water slurry gasifier with the consideration of multiple objectives is a complicated nonlinear constrained problem concerning 3 BP neural networks. In this paper, multi-objective 3-layer mixed cultural differential evolution (MO-3LM-CDE) algorithms which comprise of 4 multi-objective strategies and a 3LM-CDE algorithm are firstly presented. Then they are tested in 6 benchmark functions. Finally, the MO-3LM-CDE algorithms are applied to optimize 3 control parameters of the Texaco coal-water slurry gasifier in methanol production of a real-world chemical plant. The simulation results show that multi-objective optimal results are better than the respective single-objective optimal operations.