ABSTRACT
COVID-19 is a worldwide health threat that has resulted in a significant number of deaths and complicated healthcare management issues. To prevent the COVID-19 pandemic, there is a need to choose a safe and most effective vaccine. Several Multi-criteria Decision-Making (MADM) techniques and approaches have been selected to choose the optimal probable options. The purpose of this article is to deliver divergence measures for fuzzy sets. To validate these measures, some of the properties were also proved. The Multi-criteria Decision-Making method is employed to rank and hence select the best vaccine out of available alternatives. The proposed research allows the ranking of different vaccines based on specified criteria in a fuzzy environment to aid in the selection process. The results suggest that the proposed model provides a realistic way to select the best vaccine from the vaccines available. A case study on the selection of the best COVID-19 vaccine and its experimental results using fuzzy sets are discussed. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
Investment in education technology (EdTech) is a complex decision problem for universities during the post-Covid era. With the objective to assess the quality and adoptability of education supply chain, a novel analytical evaluation model approach is proposed, based on quality function deployment and combinative distance-based assessment. To deal with uncertainty in the evaluation process, fuzzy theory is integrated into the model. To establish the house of quality matrix, technology-based stakeholders' requirements were identified and classified in four dimensions: economic and financial, technology adoption, sustainability, competencies. Moreover, nine supplier criteria were assumed. Based on expert evaluations, the results suggest that financial credit and supplier collaboration are the most prominent attributes to evaluate suppliers, while environmental commitment is sorted as the least important criterion. The results reveal that the three dominant suppliers, which provide the best response to the identified criteria, are providers of cloud service technology. © 2022
ABSTRACT
The office of social affairs has been helping poor or marginalized families through social aid in dealing with poverty. This social aid emphasizes decreasing the poverty rate and economic recovery affected by the COVID-19 pandemic. However, the selection process in the previous year evaluated many families as aid recipient candidates through a conventional process selected by an officer. It would be vulnerable to subjectivity in assessment. Therefore, we attempted to develop a hybrid Multiple Criteria Decision-Making (MCDM) methodology to apply it to this particular decision-making process. This methodology amalgamated the DEMATEL method and the EDAS method with different tasks. Firstly, the DEMATEL method decided the feasible criteria weights automatically based on the proficient decision-maker assessment in estimating a pairwise criteria comparison. Secondly, the EDAS applied the criteria weight values to determine alternatives rank order based on the value of the appraisal score. After comparing with the VIKOR method, the hybrid DEMATEL-EDAS method demonstrated the stability and capability in dealing with the different influence parameters on the final results. © 2022 IEEE.
ABSTRACT
These days, the appraisal of the COVID-19 vulnerability has become a difficult errand for the whole world. The COVID-19 administration dynamic issue frequently includes numerous elective arrangements clashing standards. In this paper, we present a multi-criteria decision-making (MCDM) procedure based on the fuzzy VIKOR method to survey the COVID-19 vulnerability in the state of Assam, India. The trapezoidal fuzzy number is utilized to evaluate the rating of the loads for the set-up models. We have observed environment, social, and Medical factors after observing the spread of COVID-19. To study and to have comments, a committee of five experts has been formed from a different region of Assam to observe and comment to identify Coronavirus's weakest factors. For a better survey, we have divided the state into four areas namely Rural Area, Urban Area, Market Area in Rural Area, and Market Area in Urban Area. The current research looked at how the fuzzy VIKOR selects provinces for urgent adaptation needs differently than a traditional MCDM technique. © 2022 - IOS Press. All rights reserved.
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The study demonstrates the flexible functioning of the FITradeoff method that integrates the Holistic Evaluation with the Elicitation by Decomposition. For that purpose, the new features of the FITradeoff method in which integrates the two paradigms of preference modeling have been explored to solve a real multi-criteria decision problem. In this paper, a truck acquisition problem, at a midsize carrier faced with an uncertain and turbulent scenario due to the Coronavirus pandemic, was solved using the FITradeoff method. In this problem, seven criteria were considered to represent the Decision-Maker objectives. Also, six trucks (alternatives) have been examined by the Decision-Maker (Financial Director). The FITradeoff DSS supported the company as to obtain, through the combination of Holistic Evaluation and Elicitation by Decomposition, a ranking of all the trucks based on the preferences expressed during the decision process to ensure lower costs and higher profits in the long run, also guaranteeing a quicker (more efficient) resolution of the problem. © 2022, Springer Nature Switzerland AG.
ABSTRACT
Many different serological tests have been developed to support healthcare workers to identify individuals who may have developed an adaptive immune response to SARS-CoV-2. The study aimed to evaluate the test performances of the FDA EUA Authorized SARS-CoV-2 IgG antibody tests that are currently being used in coronavirus disease 2019 management. The study involved 48 SARS-CoV-2 IgG antibody tests. Different criteria of rapid diagnostic tests, plate-based tests, and immunoassay-based tests were evaluated by using multi-criteria decision making (MCDM) theory. While comparing the antibody tests, main criteria such as analytic sensitivity, specificity, positive predictive value, negative predictive value, specimen type, test technique, antigen target, time to first result, time of sampling days post infection, reagent storage conditions, practicability, etc. were assessed and used for determining the ranking of tests. The results showed that, Siemens ADVIA Centaur was the most representative of expected test performance, followed by QUANTA Flash and Siemens Dimension Vista S, while EUROIMMUN was the least favorable one. Fuzzy PROMETHEE technique can be applied in aiding decision-makers in choosing the right antibody test for the management of COVID-19. © 2021 IEEE.
ABSTRACT
In the methodology part of this study, we introduced a combined “AHP(blocks) and Entropy” approach for improving of Multi-Criteria Decision Making (MCDM) for Cloud Services (CS) selection. On this basis, we optimize the combination of professional experts’ opinion and objectivity of entropy criteria weighting. In this second part, we test our findings on an existing universal dataset with Quality of Service (QoS) and Quality of Experience (QoE) criteria and adapting for the needs of individual users and small education organisations under conditions of COVID-19 pandemics. © 2022, Springer Nature Switzerland AG.
ABSTRACT
The uncertainty in the data information for decision making is a most challenging and critical fear. In order to reduce the uncertainty in the decision making expert information for decision making problem, the Linear Diophantine fuzzy number is taking more critical part in reducing the uncertainty in information. Therefore the primary aim of this paper is to develop some different types of similarity and distance measures for linear Diophantine fuzzy numbers. With the frequent occurrence of emergency events, emergency decision making (EDM) plays a significant role in the emergency situations. It is essential for decision makers to make reliable and reasonable emergency decisions within a short time period since inappropriate decisions may result in enormous economic losses and chaotic social order. Accordingly, to ensure that EDM problems can be solved effectively and quickly, this paper proposes a new EDM method based on the novel distance and similarity measures under Linear Diophantine fuzzy (LDF) information. The similarity measure is one of the beneficial tools to determine the degree of similarity between objects. It has many crucial applications such as decision making, data mining, medical diagnosis, and pattern recognition. In this study, some novel distances and similarity measures of linear Diophantine fuzzy sets are presented. Then, the Jaccard similarity measure, exponential similarity measure, Cosine and Cotangent function based on similarity measures for LDFSs were proposed. The newly defined similarity measures are applied to medical diagnosis problem for COVID-19 virus and the results are discussed. A comparative study for the new similarity measures is established, and some advantages of the proposed work are discussed. Author
ABSTRACT
Since the beginning of the COVID-19 pandemic, the use of protective medical products has tremendously increased. The wastes generated by used products pose a threat to public health. Selection of alternative landfill sites to be determined for medical waste is a challenging task as there are several criteria to consider. Fuzzy multi-criteria decision making (MCDM) approaches can be employed to overcome this problem. In this study, the landfill sites evaluation for Covid-19 pandemic medical waste is investigated. Decision-makers give their judgments with intuitionistic fuzzy numbers and a novel circular intuitionistic fuzzy MCDM approach is developed for evaluating sites. As a contribution to the literature, this study extends the usage of circular intuitionistic fuzzy sets (C-IFS) in MCDM approaches by proposing defuzzification functions. The application of the proposed method is intended to guide future C-IFS MCDM methodologies. © 2021 IEEE.
ABSTRACT
This paper presents a combined approach based on 'AHP-block and objective criteria weighting with Entropy and Hierarchy approach for improving the methodology of Multi-Criteria Decision Making (MCDM) for Cloud Services (CS) selection. A structured and comprehensive approach allows optimizing the combination of professional experts' opinion and objectivity of entropy criteria weighting. The new method and findings are tested on an recent and detailed dataset with Quality of Service (QoS) criteria with a simulation for the needs of individual users and small education organisations under conditions of COVID-19 pandemics. © 2021 IEEE.