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.
CITATION STYLE
Saborido, R., Ruiz, A. B., Luque, M., & Miettinen, K. (2019). IRA-EMO: Interactive method using reservation and aspiration levels for evolutionary multiobjective optimization. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11411 LNCS, pp. 618–630). Springer Verlag. https://doi.org/10.1007/978-3-030-12598-1_49
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