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Selection of healthcare waste management treatment using fuzzy rough numbers and Aczel-Alsina Function.
Pamucar, Dragan; Puska, Adis; Simic, Vladimir; Stojanovic, Ilija; Deveci, Muhammet.
Afiliação
  • Pamucar D; Department of Operations Research and Statistics, Faculty of Organizational Sciences, University of Belgrade, 11000, Belgrade, Serbia.
  • Puska A; College of Engineering, Yuan Ze University, Taiwan.
  • Simic V; Government of Brcko District, Department of Public Safety, Bosnia and Herzegovina.
  • Stojanovic I; University of Belgrade, Faculty of Transport and Traffic Engineering, Vojvode Stepe 305, 11000 Belgrade, Serbia.
  • Deveci M; American University in the Emirates, Dubai International Academic City, Block 6 & 7, P.O. Box: 503000, United Arab Emirates.
Eng Appl Artif Intell ; 121: 106025, 2023 May.
Article em En | MEDLINE | ID: mdl-36908983
ABSTRACT
The COVID-19 pandemic led to an increase in healthcare waste (HCW). HCW management treatment needs to be re-taken into focus to deal with this challenge. In practice, there are several treatments of HCW with their advantages and disadvantages. This study is conducted to select the appropriate treatment for HCW in the Brcko District of Bosnia and Herzegovina. Six HCW management treatments are analyzed and observed through twelve criteria. Ten-level linguistic values were used to bring this evaluation closer to human thinking. A fuzzy rough approach is used to solve the problem of inaccuracy in determining these values. The OPA method from the Bonferroni operator is used to determine the weights of the criteria. The results of the application of this method showed that the criterion Environmental Impact ( C 4 ) received the highest weight, while the criterion Automation Level ( C 8 ) received the lowest value. The ranking of HCW management treatments was performed using MARCOS methods based on the Aczel-Alsina function. The results of this analysis showed that the best-ranked HCW management treatment is microwave (A6) while landfill treatment (A5) is ranked worst. This study has provided a new approach based on fuzzy rough numbers where the Bonferroni function is used to determine the lower and upper limits, while the application of the Aczel-Alsina function reduced the influence of decision-makers on the final decision because this function stabilizes the decision-making process.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article