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.
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Notes
- 1.
The source code is freely available at https://github.com/rsain/IRA-EMO.
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Acknowledgements
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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Saborido, R., Ruiz, A.B., Luque, M., Miettinen, K. (2019). IRA-EMO: Interactive Method Using Reservation and Aspiration Levels for Evolutionary Multiobjective Optimization. In: Deb, K., et al. Evolutionary Multi-Criterion Optimization. EMO 2019. Lecture Notes in Computer Science(), vol 11411. Springer, Cham. https://doi.org/10.1007/978-3-030-12598-1_49
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