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. doi: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

Publication year: 2017

Volume: 32

Issue number: 10

Pages range: 1172-1178

Publisher: Taylor & Francis Inc.

Publication country: United Kingdom

Publication language: English

DOI: http://doi.org/10.1080/10426914.2016.1269923

Open Access: Publication channel is not openly available

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


Last updated on 2020-17-10 at 21:26