Triangular fuzzy merec (TFMEREC) and its applications in multi criteria decision making

This paper presents a proposed method, Triangular Fuzzy MEREC (TFMEREC), which combines Triangular Fuzzy Numbers (TFNs) and Method Based on The Removal Effects of Criteria (MEREC). This integration aims to create an efficient implementation process that provides an efficient solution for complex MCDM issues, focusing on assessing halal suppliers. To demonstrate the feasibility and effectiveness of TFMEREC, this study will use an illustrative example to employ three different normalization methods with three different distance methods. Key findings from this research show that TFMEREC improves the accuracy and reliability of criteria weight determination. TFMEREC gives decision-makers more accurate weights, allowing for more informed decision-making processes. Furthermore, the sensitivity analysis provides insights into the impact of various normalization and distance methods on overall results, which improves the method's applicability and reliability. The TFMEREC method is a promising approach for dealing with imprecise and uncertain information in decision-making contexts, with potential applications in various domains. Overall, the findings underline the importance of methodological breakthroughs in enhancing decision-making processes, and the study is relevant to both experts and researchers.