A1 Journal article (refereed)
A Data-Driven Surrogate-Assisted Evolutionary Algorithm Applied to a Many-Objective Blast Furnace Optimization Problem (2017)
Chugh, T., Chakraborti, N., Sindhya, K., & Jin, Y. (2017). A Data-Driven Surrogate-Assisted Evolutionary Algorithm Applied to a Many-Objective Blast Furnace Optimization Problem. Materials and Manufacturing Processes, 32(10), 1172-1178. https://doi.org/10.1080/10426914.2016.1269923
JYU authors or editors
Publication details
All authors or editors: Chugh, Tinkle; Chakraborti, Nirupam; Sindhya, Karthik; Jin, Yaochu
Journal or series: Materials and Manufacturing Processes
ISSN: 1042-6914
eISSN: 1532-2475
Publication year: 2017
Volume: 32
Issue number: 10
Pages range: 1172-1178
Publisher: Taylor & Francis Inc.
Publication country: United Kingdom
Publication language: English
DOI: https://doi.org/10.1080/10426914.2016.1269923
Publication open access: Not open
Publication channel open access:
Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/54954
Keywords: optimisation; Pareto efficiency; iron industry
Free keywords: blast furnace; ironmaking; metamodeling; multi-objective optimization; model management; data-driven optimization; Pareto optimality
Contributing organizations
Ministry reporting: Yes
Reporting Year: 2017
JUFO rating: 1