Intuitionistic Trapezoidal Fuzzy Multiple Criteria Group Decision Making Method Based on Binary Relation

Table 3

Preference values of alternative and weights given from 3 experts by ITFN.

𝐴	𝑀	𝐶1	𝐶2
		𝐶3
𝐴1	1	⟨(0.3,0.4,0.5,0.6),(0.2,0.4,0.5,0.7)⟩	⟨(0.3,0.4,0.5,0.6),(0.2,0.4,0.5,0.7)⟩
		⟨(0.1,0.2,0.3,0.4),(0.0,0.2,0.3,0.5)⟩
	2	⟨(0.1,0.2,0.3,0.4),(0.0,0.2,0.3,0.5)⟩	⟨(0.3,0.4,0.5,0.6),(0.2,0.4,0.5,0.7)⟩
		⟨(0.0,0.1,0.2,0.3),(0.0,0.1,0.2,0.3)⟩
	3	⟨(0.3,0.4,0.5,0.6),(0.2,0.4,0.5,0.7)⟩	⟨(0.5,0.6,0.7,0.8),(0.4,0.6,0.7,0.9)⟩
		⟨(0.1,0.2,0.3,0.4),(0.0,0.2,0.3,0.5)⟩
𝐴2	1	⟨(0.5,0.6,0.7,0.8),(0.4,0.6,0.7,0.9)⟩	⟨(0.5,0.6,0.7,0.8),(0.4,0.6,0.7,0.9)⟩
		⟨(0.3,0.4,0.5,0.6),(0.2,0.4,0.5,0.7)⟩
	2	⟨(0.5,0.6,0.7,0.8),(0.4,0.6,0.7,0.9)⟩	⟨(0.7,0.8,0.9,1.0),(0.7,0.8,0.9,1.0)⟩
		⟨(0.3,0.4,0.5,0.6),(0.2,0.4,0.5,0.7)⟩
	3	⟨(0.3,0.4,0.5,0.6),(0.2,0.4,0.5,0.7)⟩	⟨(0.5,0.6,0.7,0.8),(0.4,0.6,0.7,0.9)⟩
		⟨(0.3,0.4,0.5,0.6),(0.2,0.4,0.5,0.7)⟩
𝐴3	1	⟨(0.3,0.4,0.5,0.6),(0.2,0.4,0.5,0.7)⟩	⟨(0.5,0.6,0.7,0.8),(0.4,0.6,0.7,0.9)⟩
		⟨(0.3,0.4,0.5,0.6),(0.2,0.4,0.5,0.7)⟩
	2	⟨(0.3,0.4,0.5,0.6),(0.2,0.4,0.5,0.7)⟩	⟨(0.5,0.6,0.7,0.8),(0.4,0.6,0.7,0.9)⟩
		⟨(0.1,0.2,0.3,0.4),(0.0,0.2,0.3,0.5)⟩
	3	⟨(0.5,0.6,0.7,0.8),(0.4,0.6,0.7,0.9)⟩	⟨(0.5,0.6,0.7,0.8),(0.4,0.6,0.7,0.9)⟩
		⟨(0.3,0.4,0.5,0.6),(0.2,0.4,0.5,0.7)⟩
𝐴4	1	⟨(0.7,0.8,0.9,1.0),(0.7,0.8,0.9,1.0)⟩	⟨(0.5,0.6,0.7,0.8),(0.4,0.6,0.7,0.9)⟩
		⟨(0.1,0.2,0.3,0.4),(0.0,0.2,0.3,0.5)⟩
	2	⟨(0.7,0.8,0.9,1.0),(0.7,0.8,0.9,1.0)⟩	⟨(0.5,0.6,0.7,0.8),(0.4,0.6,0.7,0.9)⟩
		⟨(0.1,0.2,0.3,0.4),(0.0,0.2,0.3,0.5)⟩
	3	⟨(0.7,0.8,0.9,1.0),(0.7,0.8,0.9,1.0)⟩	⟨(0.7,0.8,0.9,1.0),(0.7,0.8,0.9,1.0)⟩
		⟨(0.3,0.4,0.5,0.6),(0.2,0.4,0.5,0.7)⟩
Weights	1	⟨(0.3,0.4,0.5,0.6),(0.2,0.4,0.5,0.7)⟩	⟨(0.3,0.4,0.5,0.6),(0.2,0.4,0.5,0.7)⟩
		⟨(0.3,0.4,0.5,0.6),(0.2,0.4,0.5,0.7)⟩
	2	⟨(0.3,0.4,0.5,0.6),(0.2,0.4,0.5,0.7)⟩	⟨(0.3,0.4,0.5,0.6),(0.2,0.4,0.5,0.7)⟩
		⟨(0.3,0.4,0.5,0.6),(0.2,0.4,0.5,0.7)⟩
	3	⟨(0.5,0.6,0.7,0.8),(0.4,0.6,0.7,0.9)⟩	⟨(0.3,0.4,0.5,0.6),(0.2,0.4,0.5,0.7)⟩
		⟨(0.5,0.6,0.7,0.8),(0.4,0.6,0.7,0.9)⟩