Optimistic NAUTILUS navigator for multiobjective optimization with costly function evaluations

Bhupinder Singh Saini (), Michael Emmerich, Atanu Mazumdar, Bekir Afsar, Babooshka Shavazipour and Kaisa Miettinen
Additional contact information
Bhupinder Singh Saini: University of Jyvaskyla
Michael Emmerich: University of Jyvaskyla
Atanu Mazumdar: University of Jyvaskyla
Bekir Afsar: University of Jyvaskyla
Babooshka Shavazipour: University of Jyvaskyla
Kaisa Miettinen: University of Jyvaskyla

Journal of Global Optimization, 2022, vol. 83, issue 4, No 10, 865-889

Abstract: 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: Interactive methods; Multiobjective optimization problems; Decision makers; Preference information; Computational cost; Kriging (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10898-021-01119-7 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:jglopt:v:83:y:2022:i:4:d:10.1007_s10898-021-01119-7

Ordering information: This journal article can be ordered from
http://www.springer. ... search/journal/10898

DOI: 10.1007/s10898-021-01119-7

Access Statistics for this article

Journal of Global Optimization is currently edited by Sergiy Butenko

More articles in Journal of Global Optimization from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().