Assessing the Performance of Interactive Multiobjective Optimization Methods : A Survey
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
Published in
ACM Computing SurveysDate
2021Copyright
© 2021 Copyright held by the owner/author(s)
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.
...


Publisher
Association for Computing Machinery (ACM)ISSN Search the Publication Forum
0360-0300Keywords
Publication in research information system
https://converis.jyu.fi/converis/portal/detail/Publication/68770451
Metadata
Show full item recordCollections
Related funder(s)
Academy of FinlandFunding program(s)
Academy Project, AoF; Research profiles, AoF
License
Related items
Showing items with similar title or keywords.
-
Desirable properties of performance indicators for assessing interactive evolutionary multiobjective optimization methods
Aghaei Pour, Pouya; Bandaru, Sunith; Afsar, Bekir; Miettinen, Kaisa (ACM, 2022)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 ... -
LR-NIMBUS : an interactive algorithm for uncertain multiobjective optimization with lightly robust efficient solutions
Koushki, Javad; Miettinen, Kaisa; Soleimani-damaneh, Majid (Springer Science and Business Media LLC, 2022)In this paper, we develop an interactive algorithm to support a decision maker to find a most preferred lightly robust efficient solution when solving uncertain multiobjective optimization problems. It extends the interactive ... -
Optimistic NAUTILUS navigator for multiobjective optimization with costly function evaluations
Saini, Bhupinder Singh; Emmerich, Michael; Mazumdar, Atanu; Afsar, Bekir; Shavazipour, Babooshka; Miettinen, Kaisa (Springer Science and Business Media LLC, 2022)We introduce novel concepts to solve multiobjective optimization problems involving (computationally) expensive function evaluations and propose a new interactive method called O-NAUTILUS. It combines ideas of trade-off ... -
Approximation method for computationally expensive nonconvex multiobjective optimization problems
Haanpää, Tomi (University of Jyväskylä, 2012) -
A General Architecture for Generating Interactive Decomposition-Based MOEAs
Lárraga, Giomara; Miettinen, Kaisa (Springer International Publishing, 2022)Evolutionary algorithms have been widely applied for solving multiobjective optimization problems. Such methods can approximate many Pareto optimal solutions in a population. However, when solving real-world problems, a ...