An Iterative Modeling and Trust-Region Optimization Method for Batch Processes

An Iterative Modeling and Trust-Region Optimization Method for Batch Processes
复制标题

批处理的迭代建模和置信域优化方法

DOI:
10.1021/ie505064g
复制
发表时间:
2015-03
影响因子:
4.2
通讯作者:
Furong Gao
Furong Gao
中科院分区:
工程技术3区
文献类型:
--
作者:
Jinjin Zhao;Yi Yang;Xi Chen;Furong Gao

文献摘要

参考文献

相似文献

间歇过程优化在工业应用中具有重要意义。针对传统方法难以获得工业过程模型的问题,提出了一种间歇过程迭代建模与信赖域优化(IMTO)方法。提出了该方法的关键因素和IMTO算法,并进行了详细说明。该方法的特点是通过几个数值模拟,其中代理模型被用作目标函数或约束。该方法已成功地应用于注塑成型过程的质量控制和操作优化中,取得了满意的效果和较高的效率。
Batch process optimization is of great significance in industrial applications. Considering the difficulty of obtaining industrial process models in traditional methods, this paper proposes an iterative modeling and trust-region optimization (IMTO) method for batch processes. The key factors of the method and IMTO algorithm are proposed and illustrated in detail. The characteristics of the method are demonstrated through several numerical simulations, where surrogate models are used as objective functions or constraints. The proposed method is successfully implemented in the quality control and operation optimization of an injection molding process with satisfactory performance and high efficiency.
DOI: 10.1007/bf01197433
发表时间: 1997-10
期刊: Structural optimization
影响因子: --
作者:
Natalia M. Alexandrov;Mdo Branch;Nasa Larc;J. Dennis;Robert Michael Lewis;V. Torczon
通讯作者: Natalia M. Alexandrov;Mdo Branch;Nasa Larc;J. Dennis;Robert Michael Lewis;V. Torczon
DOI: 10.1142/s0129065710002516
发表时间: 2010-10
影响因子: 8
作者:
Wen Yu;Xiaoou Li
通讯作者: Wen Yu;Xiaoou Li
DOI: 10.1021/ie5017199
发表时间: 2014-10
影响因子: 4.2
作者:
Sheng Zhu;Yi Yang;Bo Yang;Zhijiang Shao;X. Chen
通讯作者: Sheng Zhu;Yi Yang;Bo Yang;Zhijiang Shao;X. Chen
DOI: 10.5555/1756006.1859919
发表时间: 2010-03
期刊: J. Mach. Learn. Res.
影响因子: --
作者:
D. Gorissen;I. Couckuyt;P. Demeester;T. Dhaene;K. Crombecq
通讯作者: D. Gorissen;I. Couckuyt;P. Demeester;T. Dhaene;K. Crombecq
DOI: 10.1021/ie030736f
发表时间: 2004-05
影响因子: 4.2
作者:
N. Lu;F. Gao;Yi Yang;Fuli Wang
通讯作者: N. Lu;F. Gao;Yi Yang;Fuli Wang