Journal
INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS
Volume 10, Issue 1, Pages 56-77Publisher
ATLANTIS PRESS
DOI: 10.2991/ijcis.2017.10.1.5
Keywords
metaheuristic; decision aid; parameter inference; indirect approach; preference analysis disaggregation
Categories
Funding
- PRODEP
- CONACYT [236154]
- program Catedras CONACyT [3058]
- CONACYT networks [269890]
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A priori incorporation of the decision maker's preferences is a crucial issue in many-objective evolutionary optimization. Some approaches characterize the best compromise solution of this problem through fuzzy outranking relations; however, they require the elicitation of a large number of parameters (weights and different thresholds). This paper proposes a novel metaheuristic-based optimization method to infer the model's parameters of a fuzzy relational system of preferences, based on a small number of judgments given by the decision maker. The results show a satisfactory rate of error when predicting new outcomes with the parameter values obtained by using small size reference sets.
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