Linguistic Distribution and Priority-Based Approximation to Linguistic Preference Relations With Flexible Linguistic...

Area of Science:

• Decision Analysis
• Computational Linguistics
• Fuzzy Logic

Background:

• Traditional preference relations struggle with linguistic vagueness and flexibility.
• Flexible linguistic expressions offer a more nuanced approach to representing preferences.
• Existing methods lack robust mechanisms for handling flexible linguistic preference data.

Purpose of the Study:

• To propose the concept of flexible linguistic preference relations (FLPRs).
• To develop a method for ranking alternatives using FLPRs.
• To explore linguistic distribution (LD) and priority-based approximation (PA) for FLPRs.

Main Methods:

• Introduced flexible linguistic preference relations (FLPRs) using flexible linguistic expressions.
• Developed a two-stage optimization process for approximating FLPRs to distribution linguistic preference relations (DLPRs).
• Derived priority vectors from DLPRs using priority-based approximation (PA).

Main Results:

• Successfully approximated FLPRs to DLPRs with minimum preference loss and maximum consistency.
• Generated priority vectors from DLPRs exhibiting desired properties.
• Demonstrated the effectiveness of the proposed method through comparative analysis.

Conclusions:

• FLPRs provide a flexible and effective framework for representing and utilizing linguistic preferences.
• The LD and PA methods enable robust ranking of alternatives based on FLPRs.
• The proposed approach offers advancements in decision-making under linguistic uncertainty.