Multiple attribute decision making model and application to food safety risk evaluation

Cross-Sectional Investigation of the Awareness and Practices of Food Safety among Food Service Catering Staff in Riyadh City Hospitals during the Coronavirus Pandemic

This study examines food safety awareness and practices among handlers in the food service sector at Riyadh City hospitals during the COVID-19 pandemic. Three hundred and fifteen (315) food service workers completed the entire questionnaire from five hospitals in Riyadh City between December 2020 and February 2021. The contributor's respondents' three-part questionnaire was divided according to general characteristics, food safety awareness, and food safety practices. The findings show that food handlers demonstrated good knowledge, techniques, and attitudes regarding maintaining food quality and ensuring food safety. Moreover, a significant positive correlation between food safety awareness and food safety practices was observed. Nevertheless, the correlation between the food handler's knowledge and safe food handling was negative. In general, our findings revealed the significance of education and the regular training of food service staff to improve learning and ensure better and safer food-handling practices, which could contribute to applying food safety practices in hospitals.

A methodology for supplier selection under the curse of dimensionality problem based on fuzzy quality function deployment and interval data envelopment analysis

Supplier selection is an important decision-making problem, which involves many quantitative and qualitative factors incorporating vagueness and imprecision. This study proposes a novel fuzzy multi-criteria decision-making framework for supplier selection, which integrates quality function deployment (QFD) and interval data envelopment analysis (DEA). The proposed methodology allows for considering the relationships among the product features and supplier evaluation criteria (SEs) and the impacts of inner dependence among SEs by constructing a house of quality (HOQ). Considering that the number of supplier evaluation indicators is greater than the number of suppliers in some cases, the curse of dimensionality problem usually exists. To solve this problem, we combine the HOQ, interval DEA models, and forward-stepwise selection approach to screen supplier evaluation indicators and select the best supplier(s). Through the two-stage supplier selection method, we can achieve the double screening of indicators and determine the final supplier(s). Finally, the application of the proposed framework is demonstrated through a numerical example and a sensitivity analysis is also carried out to verify the stability of the proposed methodology. This study focuses on supplier selection based on the combination of fuzzy QFD and interval DEA, and also provide a new two-phase methodology for DEA indicator screening.

Linguistic neutrosophic Hamacher aggregation operators and the application in evaluating land reclamation schemes for mines

Land reclamation has become a significant way for the improvement of ecological environment in mining areas. When selecting the optimal land reclamation scheme, LNNs (linguistic neutrosophic numbers) are suitable to describe the complex fuzzy evaluation information through linguistic truth, indeterminacy and falsity membership degrees. Furthermore, the Hamacher aggregation operators are good tools to handle multi-criteria decision making problems. Accordingly, the aim of this paper is to extend Hamacher aggregation operators with LNNs and then build a decision making framework for evaluating land reclamation schemes in mining areas. First, new operational laws of LNNs based on Hamacher t-norm and t-conorm are defined. Then, several linguistic neutrosophic Hamacher aggregation operators, including the linguistic neutrosophic Hamacher weighted mean aggregation operators and linguistic neutrosophic Hamacher hybrid weighted mean aggregation operators are developed. Meanwhile, their desirable properties are proved. Thereafter, a method for decision making with linguistic neutrosophic information based on these operators is proposed to deal with complex decision problems. At last, the validity of this method is confirmed by an illustrative example of evaluating the land reclamation schemes in mining areas. In addition, the impact of the parameter in extended Hamacher aggregation operators is discussed. The merits of the proposed method are also highlighted by comparing with other decision making methods. The results show that the proposed linguistic neutrosophic Hamacher aggregation operators have great flexibility and advantages, and can provide powerful ways for the evaluation of land reclamation schemes.