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Integrated MCDM Approaches for Exploring the Ideal Therapeutic Plastic Disposal Technology: Probabilistic Hesitant

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This study introduces probabilistic hesitant fuzzy sets (PHFS) to optimize healthcare plastic waste disposal (HCPWD) decisions. The approach uses the ARAS method with entropy weights to identify the most effective waste management strategies.

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Area of Science:

  • Decision Sciences
  • Environmental Management
  • Healthcare Administration

Background:

  • Efficient clinical diagnosis and management of medical waste present significant global challenges, especially in developing nations.
  • Healthcare plastic waste disposal (HCPWD) requires careful consideration of multiple qualitative factors to determine optimal strategies.
  • Existing methods may not fully capture the uncertainty and hesitancy inherent in decision-making processes for waste management.

Purpose of the Study:

  • To propose a novel multi-criteria decision-making (MCDM) framework utilizing probabilistic hesitant fuzzy sets (PHFS) for HCPWD.
  • To enhance the decision-making process by integrating the ARAS method with the entropy weighted method (EWM) for criterion weighting.
  • To apply the developed methodology to a real-world scenario for selecting the optimal healthcare waste (HCW) disposal option.

Main Methods:

  • Development of a decision-making model based on probabilistic hesitant fuzzy sets (PHFS) to handle decision-maker preferences.
  • Application of the ARAS (Additive Ratio Assessment) technique for ranking disposal alternatives.
  • Assessment of criterion weights using the entropy weighted method (EWM) proportion and score function.

Main Results:

  • The proposed PHFS-ARAS-EWM approach effectively addresses the complexities of HCPWD selection.
  • The methodology provides a robust framework for prioritizing healthcare waste disposal options based on qualitative criteria.
  • A feasibility analysis validates the practical applicability and effectiveness of the developed MCDM method for HCPWD.

Conclusions:

  • Probabilistic hesitant fuzzy sets offer a valuable extension to hesitant fuzzy sets, improving decision-making flexibility.
  • The integrated MCDM approach provides a systematic and efficient way to determine optimal HCPWD strategies.
  • This research contributes a practical tool for improving healthcare waste management and environmental protection.