Market-driven profit optimization for tabular chemical reactors with genetic algorithms

Author

Hai-Peng Qin ; Peng Chen ; Yong-Zai Lu ; Zhao-Li Wu ; Jian Chu

Author_Institution

State Key Lab. of Ind. Control Technol., Zhejiang Univ., Hangzhou, China

fYear

2012

fDate

3-5 June 2012

Firstpage

866

Lastpage

869

Abstract

With the uncertainty in the prices of feedstock, energy and finished products, the profit optimization plays a critical role in making a chemical production enterprise more dynamic and flexible to adapt the changes in global marketplace. This paper presents the development of profit optimization solution with an integration of profit model and model-based genetic algorithm (GA) optimization, and its industrial case study on an ethanolamine (EA) production line. The proposed methodology and solution may also be applied to other chemical manufacturing enterprises.

Keywords

chemical industry; chemical reactors; genetic algorithms; globalisation; profitability; GA optimization; chemical manufacturing enterprises; chemical production enterprise; energy price uncertainty; ethanolamine production line; feedstock price uncertainty; finished product price uncertainty; genetic algorithms; global marketplace; market-driven profit optimization; model-based genetic algorithm; profit model; profit optimization solution; tabular chemical reactors; Robots; Ethanolamine (EA) production; Genetic algorithms; Process model; Product-mix; Profit optimization;

fLanguage

English

Publisher

ieee

Conference_Titel

Robotics and Applications (ISRA), 2012 IEEE Symposium on

Conference_Location

Kuala Lumpur

Print_ISBN

978-1-4673-2205-8

Type

conf

DOI

10.1109/ISRA.2012.6219328

Filename

6219328