Blast furnace charging optimization using multi-objective evolutionary and genetic algorithms

Tamoghna Mitra, Frank Pettersson, Henrik Saxén, Nirupam Chakraborti

Tutkimustuotos: LehtiartikkeliArtikkeliTieteellinenvertaisarvioitu

13 Sitaatiot (Scopus)

Abstrakti

Charging programs giving rise to desired burden and gas distributions in the ironmaking blast furnace were detected through an evolutionary multi-objective optimization strategy. The Pareto optimality condition traditionally used in such studies was substituted by a recently developed k-optimality criterion that allowed for simultaneous optimization of a large number of objectives, leading to a significant improvement over the results of earlier studies. A large number of optimum charging strategies were identified through this procedure and thoroughly analyzed, in view of an efficient blast furnace operation.

AlkuperäiskieliEi tiedossa
Sivut1179–1188
JulkaisuMaterials and Manufacturing Processes
Vuosikerta32
Numero10
DOI - pysyväislinkit
TilaJulkaistu - 2017
OKM-julkaisutyyppiA1 Julkaistu artikkeli, soviteltu

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