Interval-valued intuitionistic fuzzy multi-attribute group decision-making method considering risk preference of...

Area of Science:

• Fuzzy mathematics
• Decision analysis
• Operations research

Background:

• Multi-attribute group decision-making (MAGDM) is complex, especially with uncertain information like interval-valued intuitionistic fuzzy numbers (IVIFNs).
• Determining attribute weights is challenging when information is incomplete, and decision-maker risk preferences are often overlooked.

Purpose of the Study:

• To propose an improved MAGDM method using IVIFNs that accounts for decision-maker risk preferences.
• To address situations with completely unknown attribute weight information.

Main Methods:

• Determining decision-maker weights by combining similarity and proximity.
• Introducing a risk aversion coefficient to form a group decision matrix, mitigating asymptotic behavior.
• Utilizing interval-valued intuitionistic fuzzy entropy to determine attribute and relative weights.
• Applying the TODIM method with interval-valued intuitionistic fuzzy distance measures to rank alternatives.

Main Results:

• The proposed method successfully determines decision-maker and attribute weights even with unknown information.
• Incorporating risk preference refines the decision-making process and avoids potential matrix issues.
• The method effectively calculates the superiority between schemes to identify the optimal choice.

Conclusions:

• The developed method provides a rational and effective approach for MAGDM problems with IVIFNs and unknown attribute weights.
• Considering decision-maker risk preference enhances the reliability of group decisions.
• Validated through a mechanical assembly supplier selection case study.