Informatica

Multiple Criteria Decision-Making (MCDM) is one of the most reliable and applicable decision-making tools to address real-life complex and multi-dimensional problems in accordance with the concepts of sustainable development and circular economy. Although there have been several literature reviews on several MCDM methods, there is a research gap in conducting a literature review on the Multi-Attributive Border Approximation area Comparison (MABAC) as a useful technique to deal with intelligent decision-making systems. This study attempts to present a comprehensive literature review of 117 articles on recent developments and applications of MABAC. Future outlook is provided considering challenges and current trends.

During the COVID-19 pandemic, masks have become essential items for all people to protect themselves from the virus. Because of considering multiple factors when selecting an antivirus mask, the decision-making process has become more complicated. This paper proposes an integrated approach that uses F-BWM-RAFSI methods for antivirus mask selection process with respect to the COVID-19 pandemic. Finally, sensitivity analysis was demonstrated by evaluating the effects of changing the weight coefficients of the criterion on the ranking results, simulating changes in Heronian operator parameters, and comparing the obtained solution to other MCDM approaches to ensure its robustness.