A1 Journal article (refereed)
Optimistic NAUTILUS navigator for multiobjective optimization with costly function evaluations (2022)


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


JYU authors or editors


Publication details

All authors or editors: Saini, Bhupinder Singh; Emmerich, Michael; Mazumdar, Atanu; Afsar, Bekir; Shavazipour, Babooshka; Miettinen, Kaisa

Journal or series: Journal of Global Optimization

ISSN: 0925-5001

eISSN: 1573-2916

Publication year: 2022

Publication date: 03/01/2022

Volume: 83

Issue number: 4

Pages range: 865-889

Publisher: Springer Science and Business Media LLC

Publication country: Netherlands

Publication language: English

DOI: https://doi.org/10.1007/s10898-021-01119-7

Publication open access: Openly available

Publication channel open access: Partially open access channel

Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/79299


Abstract

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.


Keywords: optimisation; multi-objective optimisation; decision making; kriging method; models (objects)

Free keywords: interactive methods; multiobjective optimization problems; decision makers; preference information; computational cost;
kriging


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Ministry reporting: Yes

Reporting Year: 2022

Preliminary JUFO rating: 2


Last updated on 2022-20-09 at 14:56