文献类型：期刊文献

英文题名：Optimal operation for 3 control parameters of Texaco coal-water slurry gasifier with MO-3LM-CDE algorithms

作者：Cao, Cuiwen[1]; Zhang, Yakun[1]; Gu, Xingsheng[1]

机构：[1] Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, 200237 Shanghai, China

年份：2013

卷号：355

起止页码：382

外文期刊名：Communications in Computer and Information Science

收录：EI(收录号：20133816757961)

语种：英文

外文关键词：Evolutionary algorithms - Coal - Parameter estimation - Chemical plants - Neural networks

摘要：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, multiobjective 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. ? Springer-Verlag Berlin Heidelberg 2013.