Multi-Objective Optimization of Pseudo-Dynamic Operation of Naphtha Pyrolysis by a Surrogate Model

作     者：Jin, Yangkun Li, Jinlong Du, Wenli Qian, Feng 

作者机构：E China Univ Sci & Technol Minist Educ Key Lab Adv Control & Optimizat Chem Proc Shanghai 200237 Peoples R China E China Univ Sci & Technol Sch Informat Sci & Engn Shanghai 200237 Peoples R China 

出 版 物：《CHEMICAL ENGINEERING & TECHNOLOGY》 (化学工程与技术)

年 卷 期：2015年第38卷第5期

页      面：900-906页

核心收录：

学科分类：0817[工学-化学工程与技术] 08[工学] 

基　　金：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] Natural Science Foundation of Shanghai [13ZR1411300] 

主　　题：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.