Multi expert cracker supplier selection using integration of circular~Pythagorean Fuzzy AHP and circular Pythagorean Fuzzy VIKOR technique

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.