Complex Intuitionistic Fuzzy Aczel-Alsina Aggregation Operators and Their Application in Multi-Attribute Decision-Making

Abstract

To handle complex, risk-illustrating, and asymmetric information, the theory discussed in this analysis is much more suitable for evaluating the above dilemmas. To manage ambiguity and inconsistency in real-life problems, the principle of Aczel–Alsina (AA) t-norm and t-conorm was initiated in 1980. These norms are massively modified and different from prevailing norms due to parameter p, where 0<p<+∞. The major contribution of this analysis is to analyze the AA operational laws (addition, multiplication, score value, accuracy value) under the complex intuitionistic fuzzy (CIF) settings. Furthermore, we initiated the principle of CIFAA weighted averaging (CIFAAWA), CIFAA ordered weighted averaging (CIFAAOWA), CIFAA hybrid averaging (CIFAAHA), CIFAA weighted geometric (CIFAAWG), CIFAA ordered weighted geometric (CIFAAOWG), CIFAA hybrid geometric (CIFAAHG), as well as their beneficial results. Additionally, to consider the elaborated works, a multi-attribute decision-making (MADM) technique was explored to investigate the supremacy and feasibility of the developed works. The main influence of this manuscript is how to choose the best decision under the availability of asymmetric types of information given by different experts. Finally, we performed the sensitivity analysis and graphically show the presented work with the help of several examples.