Elsevier

Journal of Applied Logic

Volume 10, Issue 4, December 2012, Pages 298-308
Journal of Applied Logic

Combining genetic algorithms and the finite element method to improve steel industrial processes

https://doi.org/10.1016/j.jal.2012.07.006Get rights and content
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Abstract

Most of the times the optimal control of steel industrial processes is a very complicated task because of the elevated number of parameters to adjust. For that reason, in steel plants, engineers must estimate the best values of the operational parameters of processes, and sometimes, it is also necessary to obtain the appropriate model for steel material behaviour. This article deals with three successful experiences gained from genetic algorithms and the finite element method in order to solve engineering optimisation problems. On one hand, a fully automated method for determining the best material behaviour laws is described, and on the other hand we present a common methodology to find the most appropriate settings for two cases of improvement in steel industrial processes. The study of the three reported cases allowed us to show the reliability and effectiveness of combining both techniques.

Keywords

Soft computing
Optimisation problem
Genetic algorithm
Industrial steel process
Finite element method

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