Blast furnace charging optimization using multi-objective evolutionary and genetic algorithms. Issue 10 (27th July 2017) - Mitra, Tamoghna; Pettersson, Frank; Saxén, Henrik; Chakraborti, Nirupam
ABSTRACT: 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.