Fuzzy Optimization
Mahin Ashouri; Abdollah Hadi-Vencheh; Ali Jamshidi
Abstract
Purpose: This study aims to tackle the challenging facility location selection problem in Multiple Criteria Decision Making (MCDM) scenarios, explicitly focusing on type-1 fuzzy MCDM issues. The research introduces Interval Valued Fuzzy Numbers (IVFNs) to express ratings, addressing the difficulty in ...
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Purpose: This study aims to tackle the challenging facility location selection problem in Multiple Criteria Decision Making (MCDM) scenarios, explicitly focusing on type-1 fuzzy MCDM issues. The research introduces Interval Valued Fuzzy Numbers (IVFNs) to express ratings, addressing the difficulty in determining precise membership degrees for fuzzy sets.Methodology: The proposed IVF-COPRAS method, centered on uncertainty risk reduction, is employed to enhance decision-making reliability in IVF decision problems. This methodology is applied to a real-world case involving the selection of a location for municipal wet waste landfill pits in a major Iranian city. Comparative analyses with other methods are conducted to assess the proposed approach.Findings: The study demonstrates the effectiveness of the IVF-COPRAS method in addressing facility location selection problems within MCDM. By utilizing IVFNs, the method successfully manages uncertainty, leading to more reliable decisions. Application to a practical scenario highlights the method's efficacy, and the comparative analysis provides insights into its performance relative to other methods.Originality/Value: This research contributes a novel approach with the IVF-COPRAS method for handling facility location selection challenges in MCDM. The reliance on IVFNs offers a unique perspective on uncertainty in decision-making, enhancing decision reliability. The real-world application emphasizes the method's practical significance, providing a valuable contribution to MCDM research and offering a methodological tool for similar decision-making problems across diverse domains.