Some Aczel–Alsina Power Aggregation Operators Based on Complex q-Rung Orthopair Fuzzy Set and Their Application in Multi-Attribute Group Decision-Making

Abstract

The complex q-Rung orthopair fuzzy (Cq-ROF) sets are an extended version of the fuzzy sets and q-rung orthopair fuzzy circumstances. The Cq-ROF set carried extensive information about an object with two components: membership grade (MG) and non-membership grade (NMG). The MG and NMG enlarged the unit circle to a complex plane. The decision maker evaluates complex and complicated information more accurately considering the Cq-ROF domain. This article aims to present the importance of energy sources, and we discuss the application for the selection of a suitable company selection for dam construction. Dams are the most appropriate and cheap sources to produce electricity. Now, the day’s importance of electricity is not ignorable. So, construct the multi-attribute group decision-making (MAGDM) methodology by utilizing Aczel-Alsina (AA) t-norm (TN) and t-conorm (TCN) operational laws with power aggregation operators (PAO) to solve the appropriate company selection problem for dam construction. PAO provides more accurate aggregation results between the several attributes. Finally, we define the Cq-ROF Aczel-Alsina power-weighted averaging (Cq-ROFAAPWA) and aggregation Cq-ROF Aczel-Alsina power-weighted geometric (Cq-ROFAAPWG) operators. Also, some fundamental axioms are discussed. By applying the proposed Cq-ROFAAPWA and Cq-ROFAAPWG operators, solve the real-life MAGDM problematic issue through a numerical example. For the superiority and applicability of proposed techniques, provide a comprehensive comparative analysis with other prevailing aggregation operators (AOs). In the end, provide solid conclusions.

Keywords

• q-rung orthopair fuzzy set
• complex q-rung orthopair fuzzy set
• multi-attribute group decision-making
• Aczel-Alsina t-norm and t-conorm
• aggregation operators