Optimistic NAUTILUS navigator for multiobjective optimization with costly function evaluations
| Autor: | Bhupinder Singh Saini, Michael Emmerich, Atanu Mazumdar, Bekir Afsar, Babooshka Shavazipour, Kaisa Miettinen |
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| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: |
Control and Optimization
decision makers Applied Mathematics päätöksenteko preference information Management Science and Operations Research interactive methods monitavoiteoptimointi Computer Science Applications optimointi Business Management and Accounting (miscellaneous) multiobjective optimization problems kriging mallit (mallintaminen) kriging-menetelmä computational cost |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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