An Interval-Valued Circular Intuitionistic Fuzzy MARCOS Method for Renewable Energy Source Selection

The global shift toward renewable energy has heightened the demand for precise decision-making frameworks that can effectively handle uncertainty in complex, multi-criteria evaluations. Traditional approaches often fall short in capturing the nonlinear hesitation and interval-based uncertainty present in real-world assessments. To address this challenge, this study introduces a novel decision-making framework that integrates interval-valued circular intuitionistic fuzzy sets (IVCIFSs) with the Measurement of Alternatives and Ranking according to COmpromise Solution (MARCOS) method. This hybrid approach effectively captures both interval-based uncertainty and nonlinear hesitation in expert judgments, making it particularly suitable for evaluating renewable energy sources (RES), where subjective assessments and conflicting criteria are common. To validate its practical utility, the framework was applied to a case study involving 10 RES alternatives across 7 criteria for a mid-sized Iranian food manufacturer. The analysis identified Economic Feasibility, Technical Viability, and Environmental Impact as critical criteria, with photovoltaic, biomass, and biodiesel emerging as the most favorable options. Comprehensive sensitivity and comparative analyses confirmed the model’s robustness across varying expert perspectives and its alignment with advanced multi-criteria decision-making (MCDM) methods. This study not only advances decision-making theory through the IVCIF-MARCOS integration but also offers a practical, adaptable tool for supporting effective energy transitions in uncertain and complex environments.