DefinePK

Abstract

This paper develops a robust picture fuzzy (PF) decision-making framework by integrating power aggregation operators derived from Aczél-Alsina operations. The proposed power aggregation operators effectively capture intricate interrelationships among multiple criteria, thereby enhancing the precision and reliability of decision-making processes. In this study, the familiarity of decision makers with the evaluated objects is systematically incorporated into the PF framework alongside primary data, ensuring a more comprehensive assessment. Motivated by the operational principles of Aczél-Alsina functions, this research advances the theoretical foundation of PF Aczél-Alsina power-weighted and ordered-weighted geometric operators, seamlessly integrating decision makers’ expertise into the aggregation process. The structural properties and mathematical characteristics of these newly developed operators are rigorously analyzed. To validate their practical applicability, we employ the proposed operators to solve a complex multi-criteria decision-making (MCDM) problem within the food industry, a domain where uncertainty and nuanced judgments play a critical role. A comparative evaluation against existing operators highlights the superior performance of our approach in effectively managing uncertainty, refining decision accuracy, and enhancing adaptability to real-world decision-making challenges.