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Journal of Applied Sciences
  Year: 2008 | Volume: 8 | Issue: 15 | Page No.: 2732-2738
DOI: 10.3923/jas.2008.2732.2738
 
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Response Surface Methodology and Genetic Algorithm in Optimization of Cement Clinkering Process
Maghsoud Amiri, Amir Abbas Najafi and Komeil Gheshlaghi

Abstract:
In this study, two techniques for optimization of the cement clinkering process are presented. We apply the Response Surface Methodology (RSM) and the Genetic Algorithm (GA). The response surface methodology is a traditional technique and the genetic algorithm is a new technique for experimental process optimization. The situation is to choose the best values of 4 control variables (calcium oxide, silicon dioxide, aluminum oxide and iron oxide) based on 6 quality variables (lime saturation factor, silica modulus, alumina iron modulus, hydraulic modulus, minimum burning temperature and coating index), inside a previous delimited experimental region. The techniques are performed and results compared. Results indicate that both techniques are capable of locating good conditions, but the RSM relatively reach to better solution.
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How to cite this article:

Maghsoud Amiri, Amir Abbas Najafi and Komeil Gheshlaghi, 2008. Response Surface Methodology and Genetic Algorithm in Optimization of Cement Clinkering Process. Journal of Applied Sciences, 8: 2732-2738.

DOI: 10.3923/jas.2008.2732.2738

URL: https://scialert.net/abstract/?doi=jas.2008.2732.2738

 
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