| dc.contributor.author | Chugh, Tinkle | |
| dc.contributor.author | Chakraborti, Nirupam | |
| dc.contributor.author | Sindhya, Karthik | |
| dc.contributor.author | Jin, Yaochu | |
| dc.date.accessioned | 2017-07-31T12:03:27Z | |
| dc.date.available | 2017-12-20T22:45:09Z | |
| dc.date.issued | 2017 | |
| dc.identifier.citation | 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. <i>Materials and Manufacturing Processes</i>, <i>32</i>(10), 1172-1178. <a href="https://doi.org/10.1080/10426914.2016.1269923" target="_blank">https://doi.org/10.1080/10426914.2016.1269923</a> | |
| dc.identifier.other | CONVID_26405251 | |
| dc.identifier.other | TUTKAID_72217 | |
| dc.identifier.uri | https://jyx.jyu.fi/handle/123456789/54954 | |
| dc.description.abstract | A new data-driven reference vector-guided evolutionary algorithm has been successfully implemented to construct surrogate models for various objectives pertinent to an industrial blast furnace. A total of eight objectives have been modeled using the operational data of the furnace using 12 process variables identified through a principal component analysis and optimized simultaneously. The capability of this algorithm to handle a large number of objectives, which has been lacking earlier, results in a more efficient setting of the operational parameters of the furnace, leading to a precisely optimized hot metal production process. | |
| dc.language.iso | eng | |
| dc.publisher | Taylor & Francis Inc. | |
| dc.relation.ispartofseries | Materials and Manufacturing Processes | |
| dc.subject.other | blast furnace | |
| dc.subject.other | ironmaking | |
| dc.subject.other | metamodeling | |
| dc.subject.other | multi-objective optimization | |
| dc.subject.other | model management | |
| dc.subject.other | data-driven optimization | |
| dc.subject.other | Pareto optimality | |
| dc.title | A Data-Driven Surrogate-Assisted Evolutionary Algorithm Applied to a Many-Objective Blast Furnace Optimization Problem | |
| dc.type | article | |
| dc.identifier.urn | URN:NBN:fi:jyu-201707183318 | |
| dc.contributor.laitos | Informaatioteknologian tiedekunta | fi |
| dc.contributor.laitos | Faculty of Information Technology | en |
| dc.contributor.oppiaine | Tietotekniikka | fi |
| dc.contributor.oppiaine | Mathematical Information Technology | en |
| dc.type.uri | http://purl.org/eprint/type/JournalArticle | |
| dc.date.updated | 2017-07-18T12:15:22Z | |
| dc.type.coar | http://purl.org/coar/resource_type/c_2df8fbb1 | |
| dc.description.reviewstatus | peerReviewed | |
| dc.format.pagerange | 1172-1178 | |
| dc.relation.issn | 1042-6914 | |
| dc.relation.numberinseries | 10 | |
| dc.relation.volume | 32 | |
| dc.type.version | acceptedVersion | |
| dc.rights.copyright | © 2017 Taylor & Francis. This is a final draft version of an article whose final and definitive form has been published by Taylor & Francis. Published in this repository with the kind permission of the publisher. | |
| dc.rights.accesslevel | openAccess | fi |
| dc.subject.yso | optimointi | |
| dc.subject.yso | pareto-tehokkuus | |
| dc.subject.yso | rautateollisuus | |
| jyx.subject.uri | http://www.yso.fi/onto/yso/p13477 | |
| jyx.subject.uri | http://www.yso.fi/onto/yso/p28039 | |
| jyx.subject.uri | http://www.yso.fi/onto/yso/p18241 | |
| dc.relation.doi | 10.1080/10426914.2016.1269923 | |
| dc.type.okm | A1 | |
