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Título
An integrated ELECTRE-I approach for risk evaluation with hesitant Pythagorean fuzzy information
Autor(es)
Palabras clave
Hesitant Pythagorean fuzzy sets
ELECTRE-I approach
Risk evaluation
Evaluation of health care in blood transfusion
Prevention of infant abduction
Clasificación UNESCO
12 Matemáticas
Fecha de publicación
2022
Editor
Elsevier
Citación
Akram, M., Luqman, A., & Alcantud, J. C. R. (2022). An integrated ELECTRE-I approach for risk evaluation with hesitant Pythagorean fuzzy information. Expert Systems with Applications, 200. https://doi.org/10.1016/J.ESWA.2022.116945
Resumen
[EN] Hesitant Pythagorean fuzzy sets represent a successful generalization of Pythagorean fuzzy sets that embeds
the benefits of hesitation. As such they enable the practitioner to incorporate vague data and information
very effectively. We take advantage of this feature in the procedure of risk evaluation in failure modes and
effects analysis (FMEA). This technique has demonstrated to be a powerful and valuable framework for the
identification of possible failures and the reduction of their occurrence. The advantages of hesitant Pythagorean
fuzzy sets motivate us to extend the existing methods of risk assessment in FMEA to the case where data are
in that format. Therefore, we propose an ELimination and Choice Translating REality-I (ELECTRE-I) approach
under the hesitant Pythagorean fuzzy (HPF) environment to measure and rank risks. To assess the failures,
the HPF ELECTRE-I technique creates hesitant Pythagorean fuzzy concordance/discordance matrices. Then, we
use an outranking decision graph to obtain the most crucial failure mode. We illustrate the structure of this
procedure through a flow chart. Furthermore, the model is validated through the study of real-life applications,
such as the prevention of infant abduction and risk evaluation of health care failure modes in blood transfusion.
Finally, to showcase the superiority and effectiveness of the suggested method, we provide a comprehensive
comparison of the HPF ELECTRE-I approach with existing techniques.
URI
ISSN
0957-4174
DOI
10.1016/j.eswa.2022.116945
Versión del editor
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Patrocinador
Publicación en abierto financiada por la Universidad de Salamanca como participante en el Acuerdo Transformativo CRUE-CSIC con Elsevier, 2021-2024













