A2 Review article, Literature review, Systematic review
Assessing the Performance of Interactive Multiobjective Optimization Methods : A Survey (2021)
Afsar, B., Miettinen, K., & Ruiz, F. (2021). Assessing the Performance of Interactive Multiobjective Optimization Methods : A Survey. ACM Computing Surveys, 54(4), Article 85. https://doi.org/10.1145/3448301
JYU authors or editors
Publication details
All authors or editors: Afsar, Bekir; Miettinen, Kaisa; Ruiz, Francisco
Journal or series: ACM Computing Surveys
ISSN: 0360-0300
eISSN: 1557-7341
Publication year: 2021
Volume: 54
Issue number: 4
Article number: 85
Publisher: Association for Computing Machinery (ACM)
Publication country: United States
Publication language: English
DOI: https://doi.org/10.1145/3448301
Publication open access: Not open
Publication channel open access:
Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/75333
Abstract
Interactive methods are useful decision-making tools for multiobjective optimization problems, because they allow a decision-maker to provide her/his preference information iteratively in a comfortable way at the same time as (s)he learns about all different aspects of the problem. A wide variety of interactive methods is nowadays available, and they differ from each other in both technical aspects and type of preference information employed. Therefore, assessing the performance of interactive methods can help users to choose the most appropriate one for a given problem. This is a challenging task, which has been tackled from different perspectives in the published literature. We present a bibliographic survey of papers where interactive multiobjective optimization methods have been assessed (either individually or compared to other methods). Besides other features, we collect information about the type of decision-maker involved (utility or value functions, artificial or human decision-maker), the type of preference information provided, and aspects of interactive methods that were somehow measured. Based on the survey and on our own experiences, we identify a series of desirable properties of interactive methods that we believe should be assessed.
Keywords: decision making; optimisation; multi-objective optimisation; methods; interactivity
Free keywords: multiobjective optimization problems, preference information, performance assessment, decision-makers, interactive methods
Contributing organizations
Related projects
- Decision Support for Computationally Demanding Optimization Problems
- Miettinen, Kaisa
- Research Council of Finland
- Data-driven Decision Support with Multiobjective Optimization (DAEMON)
- Miettinen, Kaisa
- Research Council of Finland
- Competitive funding to strengthen universities’ research profiles. Profiling actions at the JYU, round 3
- Hämäläinen, Keijo
- Research Council of Finland
Ministry reporting: Yes
Reporting Year: 2021
JUFO rating: 3