Journal
IEEE TRANSACTIONS ON FUZZY SYSTEMS
Volume 27, Issue 11, Pages 2163-2175Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TFUZZ.2019.2895564
Keywords
Fuzzy sets; Indexes; Decision making; Gold; Manganese; Uncertainty; Buildings; Attitude; consensus; group decision making (GDM); interval-valued intuitionistic fuzzy sets (IVIFS); trust
Funding
- National Natural Science Foundation of China [71571166, 71331002]
- Natural Science Foundation of Shanghai [18ZR1416900]
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This paper puts forward a trust-based framework for building a recommendation mechanism for consensus in group decision making with interval-valued intuitionistic fuzzy information. It first presents an attitudinal trust model where experts assign trust weights to others considering the concept of attitude of the group. This approach allows for the implementation of the group attitude in a continuous scale ranging from a pessimistic attitude to an indifferent attitude. Thus, it can express the continuous trust status, and consequently it generalizes the traditional simplified trust model: 'trusting' and 'distrusting.' In particular, three typical policies are defined as: 'extreme trust policy,' 'bounded trust policy,' and 'indifferent trust policy.' Second, the attitudinal trust induced recommendation mechanism is established by a reasonable rule: the closer the experts, the higher their trust degree. This can guarantee that the consensus level of the inconsistent expert is increased after adopting the recommended advices. In addition to group consensus, experts envisage to keep their original opinions as much as possible. A harmony degree (HD) is defined to determine the extent of the difference between an original opinion and the corresponding revised opinion after adopting the recommended advices. Combining the HD index and the consensus index, a sensitivity analysis with attitudinal parameter is proposed to verify the rationality of the proposed attitudinal trust recommendation mechanism. In practice, this will facilitate the inconsistent experts to achieve a balance between consensus degree and HD by selecting an appropriate attitudinal parameter.
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