A4 Article in conference proceedings
On Dealing with Uncertainties from Kriging Models in Offline Data-Driven Evolutionary Multiobjective Optimization (2019)


Mazumdar, A., Chugh, T., Miettinen, K., & López-Ibáñez, M. (2019). On Dealing with Uncertainties from Kriging Models in Offline Data-Driven Evolutionary Multiobjective Optimization. In K. Deb, E. Goodman, C. A. C. Coello, K. Klamroth, K. Miettinen, S. Mostaghim, & P. Reed (Eds.), Evolutionary Multi-Criterion Optimization : 10th International Conference, EMO 2019, East Lansing, MI, USA, March 10-13, 2019, Proceedings (pp. 463-474). Springer International Publishing. doi:10.1007/978-3-030-12598-1_37


JYU authors or editors


Publication details

All authors or editors: Mazumdar, Atanu; Chugh, Tinkle; Miettinen, Kaisa; López-Ibáñez, Manuel

Parent publication: Evolutionary Multi-Criterion Optimization : 10th International Conference, EMO 2019, East Lansing, MI, USA, March 10-13, 2019, Proceedings

Parent publication editors: Deb, Kalyanmoy; Goodman, Erik; Coello, Carlos A. Coello; Klamroth, Kathrin; Miettinen, Kaisa; Mostaghim, Sanaz; Reed, Patrick

ISBN: 978-3-030-12597-4

Journal or series: Lecture Notes in Computer Science

ISSN: 0302-9743

Publication year: 2019

Number in series: 11411

Pages range: 463-474

Number of pages in the book: 757

Publisher: Springer International Publishing

Publication country: Switzerland

Publication language: English

DOI: https://doi.org/10.1007/978-3-030-12598-1_37

Open Access: Publication channel is not openly available

Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/63438


Keywords: machine learning; normal distribution; multi-objective optimisation; Pareto efficiency; modelling (creation related to information)

Free keywords: Gaussian process; Pareto optimality; etamodelling; surrogate


Contributing organizations


Ministry reporting: Yes

Reporting Year: 2019

JUFO rating: 1


Last updated on 2020-18-10 at 21:06