A Survey of Fuzzy Best-Worst Group Decision-Making Process Toward Human Centricity

Efficiently harnessing group wisdom in complex decision-making domains is a crucial endeavor as socio-economic society evolves and real-life problems become increasingly intricate. The synergy of fuzzy sets, information aggregation, consensus reaching, and multicriteria decision-making (MCDM) techniques offers a versatile framework for systematically incorporating human intelligence in quantitative judgments. The Best Worst Method (BWM), a robust pairwise comparison-based MCDM technique, has gained prominence due to its distinct advantages: streamlined comparison steps, more consistent preference information, and mitigation of anchoring bias and equalizing bias. This article focuses on a comprehensive survey of advanced fuzzy set theories (including intuitionistic, neutrosophic, hesitant, Pythagorean, spherical, and Fermatean fuzzy sets), commonly used aggregation operations under fuzzy numbers (including classical mean, generalized Heronian mean, power averaging, min, and max, and ordered weighted averaging operators), and group consensus reaching process for the BWM-based decision models. A generalized algorithm for the fuzzy best-worst group decision-making (F-BWGDM) process based on a democratic-autocratic decision style is demonstrated with five performance measures, including consistency ratio, conformity, minimized violation, total deviation, and sensitivity analysis. In this survey, the technical pitfalls and application studies related to F-BWGDM are analyzed to stimulate upcoming exploration in this domain, with the ultimate goal of maintaining human group decision-making processes for qualitative assessments in a fair and systematic manner.