Multi‐Objective Optimization of Pseudo‐Dynamic Operation of Naphtha Pyrolysis by a Surrogate Model. Issue 5 (2nd April 2015)

• Record Type: Journal Article
• Authors: Jin, Yangkun; Li, Jinlong; Du, Wenli; Qian, Feng
• Is Part Of: Chemical engineering & technology. Volume 38:Issue 5(2015:May)
• Page Start: 900
• Page End: 906
• Publication Date: 2015-04-02
• Subjects: Chemical engineering -- Periodicals; Chemical processes -- Periodicals; 660.05
• DOI: 10.1002/ceat.201400162
• Languages: English
• ISSNs: 0930-7516

Abstract

<abstract abstract-type="main" xml:lang="en"> <title>Abstract</title> <p>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 <italic>ϵ</italic>‐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.</p> </abstract>