Akademik Veri Yönetim Sistemi
Operations Research Forum, cilt.7, sa.2, 2026 (Scopus)
The study proposes a theoretical framework for handling uncertainty, developed using continuous function intuitionistic fuzzy sets (CFIFSs). This framework incorporates novel elements, including Gaussian aggregation operators, a new score function, and a novel cross-entropy measure, designed to improve the processing of uncertainty. The Gaussian aggregation operators ensure smooth and flexible fusion of intuitionistic membership information. The proposed cross-entropy measure facilitates a more sensitive and consistent similarity assessment between CFIFSs. These components are integrated into a multi-criteria decision-making (MCDM) framework, where the Criteria Importance Through Intercriteria Correlation (CRITIC) method is used to determine objective criterion weights, and the Multi-Attributive Border Approximation Area Comparison (MABAC) method is adapted to operate under the CFIFS structure. The proposed approach is applied to an e-waste management problem from the literature involving the selection of Industry 4.0 technologies. The findings demonstrate that the model generates stable and interpretable rankings while providing a robust and flexible decision-making framework for managing uncertainty.