ArticleComplex & intelligent systems2021
Multi-criteria healthcare waste disposal location selection based on Fermatean fuzzy WASPAS method.
Article in Complex & intelligent systems, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- A hybrid extended Fermatean fuzzy WASPAS approach for optimal blockchain selection in building information modelling.Scientific reports · 2025Article
- Enhancing teacher recruitment and retention through decision-making models in education systems.Scientific reports · 2025Article
- Waste management in disease prevention: A public health overview.Bioinformation · 2025Article
- Fermatean fuzzy score function and distance measure based group decision making framework for household waste recycling plant location selection.Scientific reports · 2024Article
- Fermatean fuzzy distance and Sugeno-Weber operators-based SPC-MARCOS approach for sustainable supplier evaluation in the healthcare supply chain.Scientific reports · 2024Article
- Article
- A comprehensive study for selecting optimal treatment modalities for blood cancer in a Fermatean fuzzy dynamic environment.Scientific reports · 2024Article
- A novel perspective on the selection of an effective approach to reduce road traffic accidents under Fermatean fuzzy settings.PloS one · 2024Article
- Selecting the foremost big data tool to optimize YouTube data in dynamic Fermatean fuzzy knowledge.PloS one · 2024Article
- Article
- Evaluating and prioritizing the healthcare waste disposal center locations using a hybrid multi-criteria decision-making method.Scientific reports · 2023Review
- Multi-attribute decision-making based on novel Fermatean fuzzy similarity measure and entropy measure.Granular computing · 2023Article
- Fermatean Fuzzy Schweizer-Sklar Operators and BWM-Entropy-Based Combined Compromise Solution Approach: An Application to Green Supplier Selection.Entropy (Basel, Switzerland) · 2022Article
- An extended MABAC method based on prospect theory with unknown weight information under Fermatean fuzzy environment for risk investment assessment in B&R.Journal of ambient intelligence and humanized computing · 2022Article
- Interval-valued fermatean fuzzy sets with multi-criteria weighted aggregated sum product assessment-based decision analysis framework.Neural computing & applications · 2022Article
- Fermatean fuzzy copula aggregation operators and similarity measures-based complex proportional assessment approach for renewable energy source selection.Complex & intelligent systems · 2022Article
- Multicriteria decision-making based on distance measures and knowledge measures of Fermatean fuzzy sets.Granular computing · 2022Article
- Prosthetic restoration material selection using an integrated Fermatean fuzzy MCDM method.Science progressArticle
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Authors and funding
2 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Medical services inevitably generate healthcare waste (HCW) that may become hazardous to healthcare staffs, patients, the population, and the atmosphere. In most of the developing countries, HCW disposal management has become one of the fastest-growing challenges for urban municipalities and healthcare providers. Determining the location for HCW disposal centers is a relatively complex process due to the involvement of various alternatives, criteria, and strict government guidelines about the disposal of HCW. The objective of the paper is to introduce the WASPAS (weighted aggregated sum product assessment) method with Fermatean fuzzy sets (FFSs) for the HCW disposal location selection problem. This method combines the score function, entropy measure, and classical WASPAS approach within FFSs context. Next, a combined procedure using entropy and score function is proposed to estimate the criteria weights. To do this, a novel score function with its desirable properties and some entropy measures are introduced under the FFSs context. Further, an illustrative case study of the HCW disposal location selection problem on FFSs is established, which evidences the practicality and efficacy of the developed approach. Comparative discussion and sensitivity analysis are made to monitor the permanence of the introduced framework. The final results approve that the proposed methodology can effectively handle the ambiguity and inaccuracy in the decision-making procedure of HCW disposal location selection.
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