A1 Journal article (refereed)
An experimental design for comparing interactive methods based on their desirable properties (2024)
Afsar, B., Silvennoinen, J., Ruiz, F., Ruiz, A. B., Misitano, G., & Miettinen, K. (2024). An experimental design for comparing interactive methods based on their desirable properties. Annals of Operations Research, Early online. https://doi.org/10.1007/s10479-024-05941-6
JYU authors or editors
Publication details
All authors or editors: Afsar, Bekir; Silvennoinen, Johanna; Ruiz, Francisco; Ruiz, Ana B.; Misitano, Giovanni; Miettinen, Kaisa
Journal or series: Annals of Operations Research
ISSN: 0254-5330
eISSN: 1572-9338
Publication year: 2024
Publication date: 17/04/2024
Volume: Early online
Publisher: Springer Science+Business Media
Publication country: Netherlands
Publication language: English
DOI: https://doi.org/10.1007/s10479-024-05941-6
Publication open access: Openly available
Publication channel open access: Partially open access channel
Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/94448
Abstract
In multiobjective optimization problems, Pareto optimal solutions representing different tradeoffs cannot be ordered without incorporating preference information of a decision maker (DM). In interactive methods, the DM takes an active part in the solution process and provides preference information iteratively. Between iterations, the DM can learn how achievable the preferences are, learn about the tradeoffs, and adjust the preferences. Different interactive methods have been proposed in the literature, but the question of how to select the best-suited method for a problem to be solved remains partly open. We propose an experimental design for evaluating interactive methods according to several desirable properties related to the cognitive load experienced by the DM, the method’s ability to capture preferences and its responsiveness to changes in the preferences, the DM’s satisfaction in the overall solution process, and their confidence in the final solution. In the questionnaire designed, we connect each questionnaire item to be asked with a relevant research question characterizing these desirable properties of interactive methods. We also conduct a between-subjects experiment to compare three interactive methods and report interesting findings. In particular, we find out that trade-off-free methods may be more suitable for exploring the whole set of Pareto optimal solutions, while classification-based methods seem to work better for fine-tuning the preferences to find the final solution.
Keywords: optimisation; multi-objective optimisation; Pareto efficiency; decision making; decision-makers; decision support systems; interactivity; selection criteria
Free keywords: multiple criteria optimization; interactive methods; performance comparison; empirical experiments; human decision makers
Contributing organizations
Related projects
- Data-driven Decision Support with Multiobjective Optimization (DAEMON)
- Miettinen, Kaisa
- Research Council of Finland
Ministry reporting: Yes
VIRTA submission year: 2024
Preliminary JUFO rating: 1
- Computational Science (Faculty of Information Technology IT) LASK
- Multiobjective Optimization Group (Faculty of Information Technology IT) MOG
- School of Resource Wisdom (University of Jyväskylä JYU) JYU.Wisdom
- Cognitive Science (Faculty of Information Technology IT) KOG
- School of Wellbeing (University of Jyväskylä JYU) JYU.Well
- Learning and Cognitive Sciences (Faculty of Information Technology IT) LEACS