A1 Journal article (refereed)
Designing empirical experiments to compare interactive multiobjective optimization methods (2023)
Afsar, B., Silvennoinen, J., Misitano, G., Ruiz, F., Ruiz, A. B., & Miettinen, K. (2023). Designing empirical experiments to compare interactive multiobjective optimization methods. Journal of the operational research society, 74(11), 2327-2338. https://doi.org/10.1080/01605682.2022.2141145
JYU authors or editors
Publication details
All authors or editors: Afsar, Bekir; Silvennoinen, Johanna; Misitano, Giovanni; Ruiz, Francisco; Ruiz, Ana B.; Miettinen, Kaisa
Journal or series: Journal of the operational research society
ISSN: 0160-5682
eISSN: 1476-9360
Publication year: 2023
Publication date: 07/11/2022
Volume: 74
Issue number: 11
Pages range: 2327-2338
Publisher: Palgrave Macmillan
Publication country: United Kingdom
Publication language: English
DOI: https://doi.org/10.1080/01605682.2022.2141145
Publication open access: Openly available
Publication channel open access: Partially open access channel
Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/83841
Abstract
Interactive multiobjective optimization methods operate iteratively so that a decision maker directs the solution process by providing preference information, and only solutions of interest are generated. These methods limit the amount of information considered in each iteration and support the decision maker in learning about the trade-offs. Many interactive methods have been developed, and they differ in technical aspects and the type of preference information used. Finding the most appropriate method for a problem to be solved is challenging, and supporting the selection is crucial. Published research lacks information on the conducted experiments’ specifics (e.g. questions asked), making it impossible to replicate them. We discuss the challenges of conducting experiments and offer realistic means to compare interactive methods. We propose a novel questionnaire and experimental design and, as proof of concept, apply them in comparing two methods. We also develop user interfaces for these methods and introduce a sustainability problem with multiple objectives. The proposed experimental setup is reusable, enabling further experiments.
Keywords: interaction; methods; development (active); research; planning and design; decision making; comparison; usability; objectives; supporting
Free keywords: multiple objective programming; interactive methods; performance comparison; experimental study; human decision makers
Contributing organizations
Related projects
- Competitive funding to strengthen universities’ research profiles. Profiling actions at the JYU, round 3
- Hämäläinen, Keijo
- Research Council of Finland
- Data-driven Decision Support with Multiobjective Optimization (DAEMON)
- Miettinen, Kaisa
- Research Council of Finland
Ministry reporting: Yes
VIRTA submission year: 2022
JUFO rating: 2
- 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
- Decision analytics utilizing causal models and multiobjective optimization (University of Jyväskylä JYU) DEMO; 2017-2021
- Learning and Cognitive Sciences (Faculty of Information Technology IT) LEACS