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Hesitant Fuzzy Linguistic Preference Utility Set and Its Application in Selection of Fire Rescue Plans.

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Summary
This summary is machine-generated.

This study introduces a new hesitant fuzzy linguistic preference utility set to better represent decision-makers' subjective cognition in uncertain situations. This approach improves decision-making accuracy by incorporating individual sensitivities, demonstrated in emergency management fire rescue plan selection.

Keywords:
hesitant fuzzy linguistic preference utility sethesitant fuzzy linguistic preference utility-TOPSIS methodhesitant fuzzy linguistic term setlinguistic scale functionthe prospect theory

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Area of Science:

  • Decision Sciences
  • Fuzzy Logic Systems
  • Operations Research

Background:

  • Traditional hesitant fuzzy linguistic term sets struggle to capture subjective decision-maker cognition due to varying sensitivities to linguistic term semantics.
  • Existing methods lack flexibility in representing diverse decision-maker preferences, potentially leading to suboptimal outcomes in complex decision-making scenarios.
  • The cumulative prospect theory value function offers a framework to model individual sensitivities, which can be integrated into linguistic decision-making.

Purpose of the Study:

  • To propose a novel linguistic scale function and hesitant fuzzy linguistic preference utility set to accurately model decision-makers' subjective cognition.
  • To develop methods for distance measures, comparison laws, and objective weight determination for hesitant fuzzy linguistic preference utility sets.
  • To apply the proposed framework to emergency management, specifically for selecting the optimal fire rescue plan using a hesitant fuzzy linguistic preference utility-TOPSIS method.

Main Methods:

  • Development of a linguistic scale function to transform linguistic term semantics into linguistic preference values, accounting for decision-maker sensitivities.
  • Introduction of the hesitant fuzzy linguistic preference utility set for flexible expression of distinct semantics and cognition.
  • Proposal of a hesitant fuzzy linguistic preference utility-TOPSIS method, including objective attribute weight calculation, for multi-criteria decision-making.

Main Results:

  • The proposed hesitant fuzzy linguistic preference utility set effectively represents decision-makers' distinct semantics and cognitive preferences.
  • The developed hesitant fuzzy linguistic preference utility-TOPSIS method demonstrates validity in selecting the best fire rescue plan.
  • Comparative analysis confirmed the superiority of the proposed method over existing hesitant fuzzy linguistic-TOPSIS and hesitant fuzzy linguistic-VIKOR methods.

Conclusions:

  • The hesitant fuzzy linguistic preference utility set offers a significant advancement in modeling subjective cognition within uncertain decision-making environments.
  • The proposed TOPSIS method provides a robust and valid approach for complex decision problems, particularly in emergency management.
  • This research enhances the application of fuzzy linguistic decision-making by incorporating individual psychological factors for more accurate and personalized results.