Reaction modeling and optimization using neural networks and genetic algorithms

Case study involving TS-1-catalyzed hydroxylation of benzene

Somnath Nandi, P. Mukherjee, S. S. Tambe, Rajiv Kumar, B. D. Kulkarni

Research output: Contribution to journalArticle

29 Citations (Scopus)

Abstract

This paper proposes a hybrid process modeling and optimization formalism integrating artificial neural networks (ANNs) and genetic algorithms (GAs). The resultant ANN-GA strategy has the advantage that it allows process modeling and optimization exclusively on the basis of process input-output data. In the hybrid strategy, first an ANN-based process model is developed from the input-output process data. Next, the input space of the model representing process input variables is optimized using GAs, with a view to simultaneously maximize multiple process output variables. The GAs are stochastic optimization methods possessing certain unique advantages over the commonly used gradient-based deterministic algorithms. The efficacy of the hybrid formalism has been evaluated for modeling and optimizing the zeolite (TS- 1)-catalyzed benzene hydroxylation to phenol reaction whereby several sets of optimized operating conditions have been obtained. A few optimized solutions have also been subjected to the experimental verification, and the results obtained thereby matched the GA-maximized values of the three reaction output variables with a good accuracy.

Original languageEnglish (US)
Pages (from-to)2159-2169
Number of pages11
JournalIndustrial and Engineering Chemistry Research
Volume41
Issue number9
StatePublished - May 1 2002
Externally publishedYes

Fingerprint

Hydroxylation
Benzene
genetic algorithm
benzene
Genetic algorithms
Neural networks
artificial neural network
modeling
Zeolites
Phenol
zeolite
Phenols
phenol
titanium silicide

ASJC Scopus subject areas

  • Polymers and Plastics
  • Environmental Science(all)
  • Chemical Engineering (miscellaneous)

Cite this

Reaction modeling and optimization using neural networks and genetic algorithms : Case study involving TS-1-catalyzed hydroxylation of benzene. / Nandi, Somnath; Mukherjee, P.; Tambe, S. S.; Kumar, Rajiv; Kulkarni, B. D.

In: Industrial and Engineering Chemistry Research, Vol. 41, No. 9, 01.05.2002, p. 2159-2169.

Research output: Contribution to journalArticle

Nandi, Somnath ; Mukherjee, P. ; Tambe, S. S. ; Kumar, Rajiv ; Kulkarni, B. D. / Reaction modeling and optimization using neural networks and genetic algorithms : Case study involving TS-1-catalyzed hydroxylation of benzene. In: Industrial and Engineering Chemistry Research. 2002 ; Vol. 41, No. 9. pp. 2159-2169.
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