Spherical fuzzy symmetric point criterion-based approach using Aczel–Alsina prioritization: application to sustainable supplier selection

The notion of spherical fuzzy (SF) set is a potent approach to managing uncertainty and expressing expert judgments in real-life scenarios. The primary objective of this study is to formulate averaging and geometric aggregation operators (AOs) within the framework of the Aczel–Alsina (AA) operational laws, incorporating a prioritization degree based on SF information, such as SF AA prioritized average (SFAAPA) and SF AA prioritized geometric (SFAAPG) operators. Besides, we present a suite of weighted prioritized AOs, namely SF AA prioritized weighted average (SFAAPWA) and SF AA prioritized weighted geometric (SFAAPWG) operators designed to account for criteria weights while aggregating SF information. To highlight the versatility of the derived AOs, some key characteristics and notable results are also demonstrated. Afterward, an integrated weighting model is established by integrating the SF-symmetric point of criterion and SF-rank sum techniques. Following these developments, an algorithm based on proposed AOs is developed to tackle decision-making challenges with unknown weight information. By implementing the suggested approach, we examine a case study that concerns the selection of a sustainable supplier by exploiting SF data. Finally, a comparative analysis with prior scholarly works is conducted to establish the validity and practicality of the framed approach.