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Adaptative evolutionary optimization of complex processes using a kriging based genetic algorithm

Author
Abdelaleem, A.; Hjaila, K.; Espuña, A.
Type of activity
Presentation of work at congresses
Name of edition
13th Mediterranean Congress of Chemical Engineering
Date of publication
2014
Book of congress proceedings
13th Mediterranean Congress of Chemical Engineering: book of abstracts
First page
302
Last page
302
Project funding
Sistema integrado de la gestión de la energía y los recursos ambientales para procesos industriales económicamente sostenibles
URL
http://www.ub.edu/congmedit/13MCCEabstracts.pdf Open in new window
Abstract
This work presents a methodology for the optimization of chemical processes using genetic algorithm and kriging metamodels. The methodology is appropriate when the use of computationally expensive and complex processes first principle models is required (e.g. modular process simulators as ASPEN). Such models face many obstacles when used in optimization using Derivative Based Optimizers (DBO), because of the inaccurate estimation of the derivatives; moreover DBO could be easily trapped in local ...
Keywords
Krigigng, Optimization, Process Modelling
Group of research
CEPIMA - Centre d'Enginyeria de Processos i Medi Ambient

Participants

  • Abdelaleem Taha Ziez, Ahmed Shokry  (author and speaker )
  • Hjaila, Kefah  (author and speaker )
  • Espuña Camarasa, Antonio  (author and speaker )