Selecting suitable suppliers within the cracker supply chain leads to a challenging Multi-Criteria Decision-Making (MCDM) problem due to the presence of multiple, conflicting criteria such as cost, quality, distance, and reliability. Conventional models, including the integration of Pythagorean Fuzzy AHP (PF-AHP) and Pythagorean Fuzzy VIKOR (PF-VIKOR), primarily rely on linear structures. However, these methods have shortfalls in representing the circular and non-linear nature of uncertainty in expert evaluations, which can lead to imprecise outcomes. To overcome this shortfall, this research introduces a novel MCDM approach that integrates the Circular Pythagorean Fuzzy Analytic Hierarchy Process (CPF-AHP) with the Circular Pythagorean Fuzzy VIKOR (CPF-VIKOR) method for precise decision making. CPF-AHP is employed to derive the weights of evaluation criteria through circular fuzzy approach , which captures the uncertainty and inconsistency in expert opinions in a a better way. Subsequently, CPF-VIKOR is used to rank supplier alternatives by identifying a compromise solution that considers both the best possible outcome with minimal regret. The proposed CPF-based framework effectively addresses ambiguity in expert assessments and improves the accuracy of weight determination and alternative ranking. It provides a systematic and consistent approach for aggregating expert input and demonstrates superior performance compared to traditional PF-AHP and PF-VIKOR methods, particularly in handling non-linear interrelationships among decision criteria. The integration of CPF-AHP and CPF-VIKOR enhances the decision-making process for supplier selection in uncertain and complex supply chain scenarios. By effectively managing vagueness, circular aspects, and inconsistency, the proposed model delivers a more reliable and comprehensive solution. This methodology is adaptable and can be applied to other supply chain decision problems with similar complexity and uncertainty.
Maheshpraba et al. (Thu,) studied this question.