Optimization-heuristic of mechanical properties of acicular ferrite steel


Por: Cruz-Chávez M.A., Serna-Barquera S.A., Juárez-Chávez J., Romero R.J., Cruz-Rosales M.H., Campillo-Illanes B.

Publicada: 4 abr 2018
Resumen:
This paper presents two algorithms, Simulated Annealing and Iterated Local Search. Both metaheuristics use a neighborhood hybrid structure to evaluate their effectiveness and maximize the mechanical strength of microalloyed steel. Tests show that the best metaheuristic for this type of problem, which makes use of a neighborhood structure and a chemical composition, is Iterated Local Search because it gives a better mechanical strength than Simulated Annealing. Acicular Ferrite was developed in the laboratory using the best mechanical properties obtained by the heuristics in computational tests. Then the mechanical strength of the created steel was evaluated. The experimental results show that the yield strength obtained in the laboratory is comparable to that obtained in computational tests. © 2018 Elsevier B.V.

Filiaciones:
Cruz-Chávez M.A.:
 Engineering and Applied Sciences Research Center – UAEM, Av. Universidad, No. 1001, Cuernavaca, Morelos, Mexico

Serna-Barquera S.A.:
 Engineering and Applied Sciences Research Center – UAEM, Av. Universidad, No. 1001, Cuernavaca, Morelos, Mexico

Juárez-Chávez J.:
 Engineering and Applied Sciences Research Center – UAEM, Av. Universidad, No. 1001, Cuernavaca, Morelos, Mexico

 FCAeI – UAEM, Av. Universidad, No. 1001, Cuernavaca, Morelos, Mexico

Romero R.J.:
 Engineering and Applied Sciences Research Center – UAEM, Av. Universidad, No. 1001, Cuernavaca, Morelos, Mexico

Cruz-Rosales M.H.:
 FCAeI – UAEM, Av. Universidad, No. 1001, Cuernavaca, Morelos, Mexico

Campillo-Illanes B.:
 Institute of Physical Sciences/Faculty of Chemistry – UNAM, Av. Universidad, No. 1001, Cuernavaca, Morelos, Mexico
ISSN: 09215093
Editorial
Elsevier Sequoia SA, Lausanne, Switzerland, PO BOX 564, 1001 LAUSANNE, SWITZERLAND, Suiza
Tipo de documento: Article
Volumen: 721 Número:
Páginas: 65-73
WOS Id: 000430763300009