2026-10-14T15:44:27Z https://api.figshare.com/v2/oai

oai:figshare.com:article/34036846 2026-09-30T20:29:31Z category_146 category_7 category_13 category_21 category_45 category_46 category_734 category_931 category_128 portal_87 item_type_3 month_year_09_2026

A New Ranking Framework for Multi-Criteria Decision Making with Fuzzy Numbers Using Referential Alpha Cut Analysis Hamda Imam (25146097) Babita Mishra (25146100) Space Science Medicine Genetics Biotechnology Sociology Immunology Biological Sciences not elsewhere classified Information Systems not elsewhere classified Hematology Generalized trapezoidal fuzzy number(GTrFN) referential fuzzy number (RFN) TOPSIS WASPAS sensitivity analysis <p>In today’s world, intelligent systems for decision-making are continuously evolving, highlighting the importance of accurately ranking and prioritizing available alternatives. Fuzzy sets and fuzzy numbers are widely used to model complex problems, making the ranking of fuzzy numbers essential in decision-making. However, several existing score functions face difficulties in distinguishing highly overlapping fuzzy numbers and fuzzy numbers with identical cores but different support values. In some cases, these methods may also assign identical scores to distinct fuzzy numbers, resulting in ambiguous and inconsistent rankings. To address these issues, this paper proposes a novel score function based on referential fuzzy numbers to improve ranking accuracy and provide more reliable results. The proposed score function is developed from a referential fuzzy number by combining the arithmetic mean of the alpha-cut midpoints and widths to construct an uncertainty ratio, thereby incorporating both the representative value and the uncertainty of generalized trapezoidal fuzzy numbers into the ranking process. To show its effectiveness, several fuzzy numbers are evaluated and compared with existing methods. Furthermore, a Multi-Criteria Decision-Making application is solved using two modified techniques, namely modified fuzzy TOPSIS and modified WASPAS. Finally, a sensitivity analysis is conducted to evaluate the stability of the proposed method.</p> 2026-09-30T20:29:31Z Dataset Dataset 10.6084/m9.figshare.34036846.v1 https://figshare.com/articles/dataset/A_New_Ranking_Framework_for_Multi-Criteria_Decision_Making_with_Fuzzy_Numbers_Using_Referential_Alpha_Cut_Analysis/34036846 CC BY 4.0