A4 Article in conference proceedings
Desirable properties of performance indicators for assessing interactive evolutionary multiobjective optimization methods (2022)
Aghaei Pour, P., Bandaru, S., Afsar, B., & Miettinen, K. (2022). Desirable properties of performance indicators for assessing interactive evolutionary multiobjective optimization methods. In J. E. Fieldsend (Ed.), GECCO '22 : Proceedings of the Genetic and Evolutionary Computation Conference Companion (pp. 1803-1811). ACM. https://doi.org/10.1145/3520304.3533955
JYU authors or editors
Publication details
All authors or editors: Aghaei Pour, Pouya; Bandaru, Sunith; Afsar, Bekir; Miettinen, Kaisa
Parent publication: GECCO '22 : Proceedings of the Genetic and Evolutionary Computation Conference Companion
Parent publication editors: Fieldsend, Jonathan E.
Place and date of conference: Boston, Massachusetts, USA, 9.-13.7.2022
ISBN: 978-1-4503-9268-6
Publication year: 2022
Publication date: 19/07/2022
Pages range: 1803-1811
Number of pages in the book: 2345
Publisher: ACM
Publication country: United States
Publication language: English
DOI: https://doi.org/10.1145/3520304.3533955
Publication open access: Openly available
Publication channel open access: Partially open access channel
Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/83772
Abstract
Interactive methods support decision makers in finding the most preferred solution in multiobjective optimization problems. They iteratively incorporate the decision maker's preference information to find the best balance among conflicting objectives. Several interactive methods have been developed in the literature. However, choosing the most suitable interactive method for a given problem can prove challenging and appropriate indicators are needed to compare interactive methods. Some indicators exist for a priori methods, where preferences are provided at the beginning of the solution process. We present some numerical experiments that illustrate why these indicators are not suitable for interactive methods. As the main contribution of this paper, we propose a set of desirable properties of indicators for assessing interactive methods as the first step of filling a gap in the literature. We discuss each property in detail and provide simple examples to illustrate their behavior.
Keywords: multi-objective optimisation; optimisation; decision making; decision support systems; interactivity; indicators
Free keywords: multiple criteria optimization; performance evaluation; performance assessment; interactive methods; metrics; performance; multi-criterion optimization and decision-making
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
Reporting Year: 2022
JUFO rating: 1