Application of novel intuitionistic fuzzy BWAHP process for analysing the efficiency of water treatment plant

HOUSING PREFERENCE STRUCTURES IN EAST ASIA: AN EMPIRICAL STUDY AND NON-PARADIGMATIC SHIFTS BETWEEN NEARBY METROPOLES

A systematic research flow was applied to the Southern Metropolis in Taiwan not only to recount residents’ considerations in this cultural area but also to compare them with those of other metropolitans on the island in relation to general housing concerns. The constructs and factors in housing decision-making were justified using the literature, confirmed with experts in the field, and organised as a decision hierarchy that formed the foundation of a survey. The investigation combined the analytic hierarchy process and Student’s t-test, both of which are credible methods, to facilitate a grounded process for mind mining. The importance of constructs/factors were thus assessed on a numerical basis, and a set of unforeseen insights were explored for the different parties of interest (e.g., buyers, construction companies, agents, asset managers, etc.). Opinion gaps between different sample groups were identified. This set of empirical knowledge filled the gap in the literature. It is noteworthy that among the constructs in the region studied, (housing) ‘conditions’ dominated ‘price’, while ‘location and transport’ was the least important. A ‘non-paradigmatic shift’ in people’s total housing preference structure, which changed gradually with decreasing population density and increasing plain geography from the north to the south between nearby metropoles, was observed, despite the niche but commensurable cultural norm in East Asia being the overall scenario of the island. Some existing claims about the housing preferences in this area were also either supported or rebutted by the quantitative evidence(s).

A Fuzzy Extension of Simplified Best-Worst Method (F-SBWM) and Its Applications to Decision-Making Problems

Today, most of the issues and challenges faced by managers and decision makers are complex and multifaceted. More clearly, due to the developments of technologies, emerging trends in various industries, competitive markets, and rapid and transformative changes in the business environment, managers and decision makers have faced an uncertain environments and issues that cannot be resolved definitively. The use of multi-criteria decision-making (MCDM) methods as a practical and decision-supporting tool allows managers to examine decision-making issues in various organizations and industries based on various criteria, alternatives, and objectives and make decisions with greater reliability. The use of fuzzy techniques and concepts in MCDM methods and their mathematical relationships makes it possible to consider complexities and uncertainties in decisions related to various issues and it can lead to better and more realistic decisions. In this paper, the simplified best-worst method (SBWM), which is one of the methods based on pairwise comparisons, has been developed using triangular fuzzy numbers (TFNs) to propose a fuzzy extension of SBWM (F-SBWM). Triangular fuzzy numbers in different symmetric and asymmetric forms have widely been used in MCDM approaches and pairwise comparisons. It is noteworthy that symmetric numbers are used when we are using equal division of the domain due to an increased ambiguity and lack of information. The proposed approach as a simplified fuzzy MCDM method helps managers and decision makers in various industries to solve decision-making problems under uncertainty without the need for complex calculations, specialized skills, and software packages. To check the feasibility and applicability of the proposed approach, two numerical examples and a computational experiment with real data are presented, and the results are analyzed and discussed. Furthermore, to check the robustness of the results obtained from the proposed approach, sensitivity analysis and comparison of methods have been performed.

An extended MAIRCA method using intuitionistic fuzzy sets for coronavirus vaccine selection in the age of COVID-19

All over the world, the COVID-19 outbreak seriously affects life, whereas numerous people have infected and passed away. To control the spread of it and to protect people, appreciable vaccine development efforts continue with increasing momentum. Given that this pandemic will be in our lives for a long time, it is obvious that a reliable and useful framework is needed to choose among coronavirus vaccines. To this end, this paper proposes a new intuitionistic fuzzy extension of MAIRCA framework, named intuitionistic fuzzy MAIRCA (IF-MAIRCA) to assess coronavirus vaccines according to some evaluation criteria. Based on the group decision-making, the IF-MAIRCA framework both extracts the criteria weights and discovers the prioritization of the alternatives under uncertainty. In this work, as a case study, five coronavirus vaccines approved by the world's leading authorities are evaluated according to various criteria. The findings demonstrate that the most significant criteria considered in coronavirus vaccine selection are “duration of protection,” “effectiveness of the vaccine,” “success against the mutations,” and “logistics,” respectively, whereas the best coronavirus vaccine is AZD1222. Apart from this, the proposed model's robustness is verified with a three-phase sensitivity analysis.