NAUTILI: A trade-off-free interactive multiobjective optimization method for group decision making

Abstract We consider problems with multiple conflicting objective functions and multiple decision makers and concentrate on interactive methods, where the preferences of the decision makers are iteratively incorporated in the solution process. We propose a novel trade-off-free interactive multiobjective optimization method NAUTILI for group decision making. In NAUTILI, the solution process starts from an inferior solution. Then, each decision maker individually interacts with NAUTILI via specialized visualizations in a graphical user interface to provide their preferences. NAUTILI determines the direction of simultaneous improvements for the whole group. Thus, in each iteration, all decision makers gain in all objective functions until reaching the most preferred solution by the group. This solution is so-called Pareto optimal. The method can be seen as a win-win approach, as in each iteration, all the objective functions can be improved simultaneously for all decision makers. As a proof of concept, we demonstrate the potential and benefits of NAUTILI with a forest management problem involving three decision makers. We also asked the decision makers to answer a questionnaire about their satisfaction with the final solution, the method’s user-friendliness, and how they felt that their preferences were reflected in the solution process. The findings support the applicability of the method. This supports the potential of applying an interactive and trade-off-free method to group decision making in multiobjective optimization.

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Publication Details

Journal
Journal of Global Optimization
Published
2026-05-27
DOI
https://doi.org/10.1007/s10898-026-01617-6
Primary Topic
Advanced Multi-Objective Optimization Algorithms
Type
article
Field-Weighted Citation Impact
0.00

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article

NAUTILI: A trade-off-free interactive multiobjective optimization method for group decision making

Babooshka Shavazipour, Kaisa Miettinen, Dmitry Podkopaev, Bhupinder Singh Saini et al.
Journal of Global Optimization
Advanced Multi-Objective Optimization Algorithms
article

NAUTILI: A trade-off-free interactive multiobjective optimization method for group decision making

Babooshka Shavazipour, Kaisa Miettinen, Dmitry Podkopaev, Bhupinder Singh Saini, Francisco Ruiz, Juuso Pajasmaa
article en

Abstract

Abstract We consider problems with multiple conflicting objective functions and multiple decision makers and concentrate on interactive methods, where the preferences of the decision makers are iteratively incorporated in the solution process. We propose a novel trade-off-free interactive multiobjective optimization method NAUTILI for group decision making. In NAUTILI, the solution process starts from an inferior solution. Then, each decision maker individually interacts with NAUTILI via specialized visualizations in a graphical user interface to provide their preferences. NAUTILI determines the direction of simultaneous improvements for the whole group. Thus, in each iteration, all decision makers gain in all objective functions until reaching the most preferred solution by the group. This solution is so-called Pareto optimal. The method can be seen as a win-win approach, as in each iteration, all the objective functions can be improved simultaneously for all decision makers. As a proof of concept, we demonstrate the potential and benefits of NAUTILI with a forest management problem involving three decision makers. We also asked the decision makers to answer a questionnaire about their satisfaction with the final solution, the method’s user-friendliness, and how they felt that their preferences were reflected in the solution process. The findings support the applicability of the method. This supports the potential of applying an interactive and trade-off-free method to group decision making in multiobjective optimization.

Journal of Global Optimization
Systems Research Institute (PL), Universidad de Málaga (ES), University of Jyväskylä (FI), Polish Academy of Sciences (PL)
European Commission, Academy of Finland, Jyväskylän Yliopisto, European Regional Development Fund, Agencia Estatal de Investigación
Peace, Justice and strong institutions
Openalex Percentile: Top 4%
Advanced Multi-Objective Optimization Algorithms
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