An Intelligent Fuzzy MCDM Model Based on D and Z Numbers for Paver Selection: IMF D-SWARA—Fuzzy ARAS-Z Model

One of the most important challenges when building road infrastructure is selection appropriate mechanization, on which efficiency construction and life exploitation depends largely. As machinery, pavers occupy a significant place in civil engineering projects, so their selection, depending category, very activity. The objective this paper to develop an intelligent Fuzzy MCDM (Multi-Criteria Decision-Making) model, consists integration D Z numbers for machinery. IMF D-SWARA (Improved Step-Wise Weight Assessment Ratio Analysis) method was used determine weighting coefficients. A novel ARAS-Z (Additive Assessment) has been developed adequate paver lower category roads (asphalt width up 5 m), represents contribution novelty paper. total 10 alternatives were evaluated based 16 criteria classified into 4 main groups. results have shown that alternative A8—SUPER 1300-3 with best characteristics considered set parameters. After that, verification tests calculated, they include comparative analysis four other methods numbers, change normalization procedure, impact changing size initial fuzzy matrix. showed stability model negligible deviations.