Blast furnace charging optimization using multi-objective evolutionary and genetic algorithms. Issue 10 (27th July 2017)

• Record Type: Journal Article
• Authors: Mitra, Tamoghna; Pettersson, Frank; Saxén, Henrik; Chakraborti, Nirupam
• Is Part Of: Materials and manufacturing processes. Volume 32:Issue 10(2017)
• Page Start: 1179
• Page End: 1188
• Publication Date: 2017-07-27
• Subjects: Blast furnace -- burden distribution -- charging -- genetic algorithms -- multi-objective optimization; Manufacturing processes -- Periodicals; Materials -- Periodicals; Manufactured Materials; 670.5
• DOI: 10.1080/10426914.2016.1257133
• Languages: English
• ISSNs: 1042-6914

Abstract

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.