TY - JOUR
T1 - A novel multi-criteria group decision-making method for heterogeneous and dynamic contexts using multi-granular fuzzy linguistic modelling and consensus measures
AU - Morente-Molinera, J. A.
AU - Wu, X.
AU - Morfeq, A.
AU - Al-Hmouz, R.
AU - Herrera-Viedma, E.
N1 - Funding Information:
This project was funded by the Deanship of Scientific Research (DSR), King Abdulaziz University, Jeddah, Saudi Arabia, under grant no. (KEP-7-135-39). The authors, therefore, acknowledge with thanks DSR technical and financial support.
Funding Information:
This project was funded by the Deanship of Scientific Research ( DSR ), King Abdulaziz University, Jeddah, Saudi Arabia, under grant no. ( KEP-7-135-39 ). The authors, therefore, acknowledge with thanks DSR technical and financial support.
Publisher Copyright:
© 2019 Elsevier B.V.
PY - 2020/1
Y1 - 2020/1
N2 - This paper presents a novel multi-criteria group decision-making method that is capable of working in heterogeneous and dynamic environments. It is applicable in non-static frameworks where the decision context can vary at any time during the process. It also makes experts comfortable by allowing them to provide information using their most preferred means. By using multi-granular fuzzy linguistic modelling, the experts can provide preferences using their preferred linguistic label set. Furthermore, they also can choose the criteria values that they want to provide preferences for. Also, experts, alternatives and criteria can be added at any time during the decision process. Finally, consensus measures are applied in order to promote further debate and to help the experts reach an agreement.
AB - This paper presents a novel multi-criteria group decision-making method that is capable of working in heterogeneous and dynamic environments. It is applicable in non-static frameworks where the decision context can vary at any time during the process. It also makes experts comfortable by allowing them to provide information using their most preferred means. By using multi-granular fuzzy linguistic modelling, the experts can provide preferences using their preferred linguistic label set. Furthermore, they also can choose the criteria values that they want to provide preferences for. Also, experts, alternatives and criteria can be added at any time during the decision process. Finally, consensus measures are applied in order to promote further debate and to help the experts reach an agreement.
KW - Computing with words
KW - Consensus measures
KW - Multi-criteria group decision-making
KW - Multi-granular fuzzy linguistic modelling
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U2 - 10.1016/j.inffus.2019.06.028
DO - 10.1016/j.inffus.2019.06.028
M3 - Article
AN - SCOPUS:85068233716
SN - 1566-2535
VL - 53
SP - 240
EP - 250
JO - Information Fusion
JF - Information Fusion
ER -