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Medical waste disposal planning for healthcare units using spherical fuzzy CRITIC-WASPAS.

Authors :
Menekşe, Akın
Camgöz Akdağ, Hatice
Source :
Applied Soft Computing; Sep2023, Vol. 144, pN.PAG-N.PAG, 1p
Publication Year :
2023

Abstract

Healthcare services create medical waste that may be dangerous to healthcare personnel, patients, the general public, and the environment. Medical waste disposal method selection is among the most important decisions that must be made by healthcare organizations, and such a problem has a number of contradictory criteria and alternatives. On the other hand, decision experts may have considerable uncertainty while evaluating these alternatives. In this paper, new fuzzy multi-criteria decision-making (MCDM) methodologies are provided for assessing the medical waste disposal alternatives. The CRiteria Importance Through Intercriteria Correlation (CRITIC) is used for obtaining criterion weights in an objective manner, and the Weighted Aggregated Sum Product ASsessment (WASPAS) approach is utilized to rank the alternatives. For modeling the uncertainty in the nature of the problem, the proposed methodology is developed in single and interval-valued spherical fuzzy environments. Single-valued spherical fuzzy sets enable users to model the membership, non-membership, and hesitancy parameters independently. On the other hand, interval-valued spherical fuzzy sets provide increased fuzziness modeling capacity. The step-by-step solution of the proposed methodologies are followed by sensitivity and comparative analyses, and a discussion. This study contributes to the work of both academics and practitioners in the healthcare industry, as well as other sectors facing similar types of decision-making problems. • CRITIC-WASPAS method is extended with single and interval-valued spherical fuzzy sets. • The proposed methodology provides extensive fuzziness modeling capacity. • The CRITIC phase enables calculating criteria weights in an objective manner. • Medical waste disposal alternatives are prioritized with the WASPAS technique. • Sensitivity analyses for decision expert, criterion, and threshold parameter weights are provided. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15684946
Volume :
144
Database :
Supplemental Index
Journal :
Applied Soft Computing
Publication Type :
Academic Journal
Accession number :
164927035
Full Text :
https://doi.org/10.1016/j.asoc.2023.110480