文献类型：期刊文献

英文题名：Multi-Objective Optimization of Pseudo-Dynamic Operation of Naphtha Pyrolysis by a Surrogate Model

作者：Jin, Yangkun[1];Li, Jinlong[2];Du, Wenli[1];Qian, Feng[1]

机构：[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, Sch Informat Sci & Engn, Shanghai 200237, Peoples R China

年份：2015

卷号：38

期号：5

起止页码：900

外文期刊名：CHEMICAL ENGINEERING & TECHNOLOGY

收录：;EI(收录号：20151500730310);WOS:【SCI-EXPANDED(收录号:WOS:000353515100017)】；

基金：This work was supported by the Major State Basic Research Development Program of China (2012CB720500), National Natural Science Foundation of China (U1162202, 21276078), Fundamental Research Funds for the Central Universities, Shanghai Rising-Star Program (13QH1401200), and Natural Science Foundation of Shanghai (13ZR1411300).

语种：英文

外文关键词：epsilon-Constraint method; Multi-objective optimization; Naphtha pyrolysis process; Surrogate model

摘要：A simple pseudo-dynamic surrogate model is developed in the framework of the state space model with the feed-forward neural network to replace the complex free radical pyrolysis model. The surrogate model is then applied to investigate the multi-objective optimization of two key performance objectives with distinct contradiction: the mean yields of key products and the day mean profits. The epsilon-constraint method is employed to solve the multi-objective optimization problem, which provides a broad range of operation conditions depicting tradeoffs of both key objectives. The Pareto-optimal frontier is successfully obtained and five selected cases on the frontier are discussed, suggesting that flexible operations can be performed based on industrial demands.