ArticleComputers & industrial engineering2022
A novel hybrid multi-criteria group decision-making approach with intuitionistic fuzzy sets to design reverse supply chains for COVID-19 medical waste recycling channels.
Article in Computers & industrial engineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed.
- Article
- Intermodal travel planning and decision support integrated with transportation and energy systems.Heliyon · 2024Article
- An application of BWM for risk control in reverse logistics of medical waste.Frontiers in public health · 2024Article
- Risk Management for Whole-Process Safe Disposal of Medical Waste: Progress and Challenges.Risk management and healthcare policy · 2024Review
- The effect of COVID-19 on nuclear medicine and radiopharmacy activities: A global survey.Scientific reports · 2023Article
- Assessment of sustainable waste management alternatives using the extensions of the base criterion method and combined compromise solution based on the fuzzy Z-numbers.Environmental science and pollution research international · 2023Article
- Does COVID-19 impact on financial markets of China-evidence from during and pre-COVID-19 outbreak.Environmental science and pollution research international · 2023Article
- Application of Capital Asset Pricing Model Based on BP Neural Network in E-commerce Financing.Computational intelligence and neuroscience · 2022Article
- Modeling analysis of the correlation between duality innovation and multinational enterprise performance.Frontiers in psychology · 2022Article
- Implementation of Trusted Traceability Query Using Blockchain and Deep Reinforcement Learning in Resource Management.Computational intelligence and neuroscience · 2022Article
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Authors and funding
5 authors.
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No grant is acknowledged in the PubMed record.
Abstract
The COVID-19 pandemic has led to exponential growth in COVID-19 medical waste (CMW) generation worldwide. This tremendous growth in CMW is a major transmission medium for COVID-19 virus and thus brings serious challenges to medical waste (MW) management. Designing an efficient and reliable CMW reverse supply chain in this situation can help to prevent epidemic spread. Nowadays, the assessment of CMW recycling channels has become a challenging mission for health-care institutions, especially in developing countries. It can be seen as a complex multi-criteria group decision-making (MCGDM) problem that requires the consideration of multiple conflicting tangible and intangible criteria. Nevertheless, few academics have been concerned about this issue. Moreover, current MCGDM methods have limited support for CMW recycling channel evaluation and they do not consider hospitals' reverse supply chain strategy when evaluating. Thus, this study presents a novel MCGDM approach based on intuitionistic fuzzy sets (IFSs) and the VIKOR method for assessing the capacity of CWM recycling channels. According to the characteristics of CMW, processing flow and the TOE (Technology, Organization and Environment) theoretical framework, we established a new CMW recycling channel capacity evaluation index system which makes our proposed method more targeted and efficient. In the decision-making process, we integrate the best-worst method (BWM) and entropy to determine the decision makers (DMs) weighting in a more comprehensive way, considering both subjective and objective criteria, which was ignored by many MCGDM methods. A new aggregation operator called IFWA is proposed by us, considering the priority of DMs. Based on both the ranking of capacity and disposal charges, we then position the alternatives in the recycling channel priority index (RCPI) matrix constructed by us. According to this PCPI matrix and the reverse supply chain strategy of hospitals, a more reasonable CMW allocation strategy is determined and a more efficient CMW reverse supply chain is designed. Finally, a real case study from Wuhan was examined to illustrate the validation of our approach.
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