Title :
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
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;
Conference_Titel :
Robotics and Applications (ISRA), 2012 IEEE Symposium on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4673-2205-8
DOI :
10.1109/ISRA.2012.6219328
