On Dealing with Uncertainties from Kriging Models in Offline Data-Driven Evolutionary Multiobjective Optimization
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. Lecture Notes in Computer Science, 11411. https://doi.org/10.1007/978-3-030-12598-1_37
Julkaistu sarjassa
Lecture Notes in Computer ScienceToimittajat
Päivämäärä
2019Oppiaine
TietotekniikkaLaskennallinen tiedeMultiobjective Optimization GroupMathematical Information TechnologyComputational ScienceMultiobjective Optimization GroupTekijänoikeudet
© Springer Nature Switzerland AG 2019
Many works on surrogate-assisted evolutionary multiobjective optimization have been devoted to problems where function evaluations are time-consuming (e.g., based on simulations). In many real-life optimization problems, mathematical or simulation models are not always available and, instead, we only have data from experiments, measurements or sensors. In such cases, optimization is to be performed on surrogate models built on the data available. The main challenge there is to fit an accurate surrogate model and to obtain meaningful solutions. We apply Kriging as a surrogate model and utilize corresponding uncertainty information in different ways during the optimization process. We discuss experimental results obtained on benchmark multiobjective optimization problems with different sampling techniques and numbers of objectives. The results show the effect of different ways of utilizing uncertainty information on the quality of solutions.
Julkaisija
Springer International PublishingEmojulkaisun ISBN
978-3-030-12597-4Konferenssi
International Conference on Evolutionary Multi-Criterion OptimizationKuuluu julkaisuun
Evolutionary Multi-Criterion Optimization : 10th International Conference, EMO 2019, East Lansing, MI, USA, March 10-13, 2019, ProceedingsISSN Hae Julkaisufoorumista
0302-9743Asiasanat
Julkaisu tutkimustietojärjestelmässä
https://converis.jyu.fi/converis/portal/detail/Publication/28954673
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