Optimistic NAUTILUS navigator for multiobjective optimization with costly function evaluations
Saini, B. S., Emmerich, M., Mazumdar, A., Afsar, B., Shavazipour, B., & Miettinen, K. (2022). Optimistic NAUTILUS navigator for multiobjective optimization with costly function evaluations. Journal of Global Optimization, 83(4), 865-889. https://doi.org/10.1007/s10898-021-01119-7
Julkaistu sarjassa
Journal of Global OptimizationTekijät
Päivämäärä
2022Oppiaine
Multiobjective Optimization GroupLaskennallinen tiedeTietojärjestelmätiedePäätöksen teko monitavoitteisestiMultiobjective Optimization GroupComputational ScienceInformation Systems ScienceDecision analytics utilizing causal models and multiobjective optimizationTekijänoikeudet
© The Author(s) 2021
We introduce novel concepts to solve multiobjective optimization problems involving (computationally) expensive function evaluations and propose a new interactive method called O-NAUTILUS. It combines ideas of trade-off free search and navigation (where a decision maker sees changes in objective function values in real time) and extends the NAUTILUS Navigator method to surrogate-assisted optimization. Importantly, it utilizes uncertainty quantification from surrogate models like Kriging or properties like Lipschitz continuity to approximate a so-called optimistic Pareto optimal set. This enables the decision maker to search in unexplored parts of the Pareto optimal set and requires a small amount of expensive function evaluations. We share the implementation of O-NAUTILUS as open source code. Thanks to its graphical user interface, a decision maker can see in real time how the preferences provided affect the direction of the search. We demonstrate the potential and benefits of O-NAUTILUS with a problem related to the design of vehicles.
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Julkaisija
Springer Science and Business Media LLCISSN Hae Julkaisufoorumista
0925-5001Asiasanat
Julkaisu tutkimustietojärjestelmässä
https://converis.jyu.fi/converis/portal/detail/Publication/103601972
Metadata
Näytä kaikki kuvailutiedotKokoelmat
Rahoittaja(t)
Suomen AkatemiaRahoitusohjelmat(t)
Akatemiahanke, SA; Profilointi, SALisätietoja rahoituksesta
This research was partly funded by the Academy of Finland (Grants 322221 and 311877). The research is related to the thematic research area Decision Analytics utilizing Causal Models and Multiobjective Optimization (DEMO), jyu.fi/demo, at the University of Jyväskylä.Lisenssi
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