IRA-EMO : Interactive Method Using Reservation and Aspiration Levels for Evolutionary Multiobjective Optimization
Abstract
We propose a new interactive evolutionary multiobjective optimization method, IRA-EMO. At each iteration, the decision maker (DM) expresses her/his preferences as an interesting interval for objective function values. The DM also specifies the number of representative Pareto optimal solutions in these intervals referred to as regions of interest one wants to study. Finally, a real-life engineering three-objective optimization problem is used to demonstrate how IRA-EMO works in practice for finding the most preferred solution.
Main Authors
Format
Conferences
Conference paper
Published
2019
Series
Subjects
Publication in research information system
Publisher
Springer International Publishing
The permanent address of the publication
https://urn.fi/URN:NBN:fi:jyu-201903071764Use this for linking
Parent publication ISBN
978-3-030-12597-4
Review status
Peer reviewed
ISSN
0302-9743
DOI
https://doi.org/10.1007/978-3-030-12598-1_49
Conference
International Conference on Evolutionary Multi-Criterion Optimization
Language
English
Published in
Lecture Notes in Computer Science
Is part of publication
Evolutionary Multi-Criterion Optimization : 10th International Conference, EMO 2019, East Lansing, MI, USA, March 10-13, 2019, Proceedings
Citation
- Saborido, R., Ruiz, A. B., Luque, M., & Miettinen, K. (2019). IRA-EMO : Interactive Method Using Reservation and Aspiration Levels for Evolutionary Multiobjective Optimization. In K. Deb, E. Goodman, C. A. C. Coello, K. Klamroth, K. Miettinen, S. Mostaghim, & P. Reed (Eds.), Evolutionary Multi-Criterion Optimization : 10th International Conference, EMO 2019, East Lansing, MI, USA, March 10-13, 2019, Proceedings (pp. 618-630). Springer International Publishing. Lecture Notes in Computer Science, 11411. https://doi.org/10.1007/978-3-030-12598-1_49
License
Funder(s)
Research Council of Finland
Funding program(s)
Akatemiahanke, SA
Academy Project, AoF
Additional information about funding
This research is funded by the Spanish Government (ECO2017-88883-R and ECO2017-90573-REDT), the Andalusian Regional Government (SEJ-532) and the Academy of Finland (project 287496). Ana B. Ruiz thanks the post-doctoral fellowship “Captación de Talento para la Investigación” at the Univ. of Málaga. The research is related to thematic research area DEMO (Univ. of Jyvaskyla).
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