Prioritization of low-carbon suppliers based on Pythagorean fuzzy group decision making with self-confidence level

Figures & data

Table 1. PF decision matrix for expert 1.

	$C_1$	$C_2$	$C_3$	$C_4$	$C_5$
$A_1$	$〈0.5,(0.6,0.6)〉$	$〈0.7,(0.8,0.6)〉$	$〈0.8,(0.4,0.7)〉$	$〈0.5,(0.8,0.1)〉$	$〈0.3,(0.9,0.2)〉$
$A_2$	$〈0.4,(0.5,0.7)〉$	$〈0.7,(0.3,0.8)〉$	$〈0.5,(0.7,0.7)〉$	$〈0.6,(0.4,0.8)〉$	$〈0.2,(0.5,0.4)〉$
$A_3$	$〈0.2,(0.5,0.4)〉$	$〈0.6,(0.6,0.4)〉$	$〈0.8,(0.7,0.6)〉$	$〈0.5,(0.5,0.7)〉$	$〈0.4,(0.9,0.2)〉$
$A_4$	$〈0.7,(0.8,0.3)〉$	$〈0.7,(0.3,0.4)〉$	$〈0.5,(0.4,0.5)〉$	$〈0.3,(0.4,0.6)〉$	$〈0.5,(0.6,0.6)〉$

Table 2. PF decision matrix for expert 2.

	$C_1$	$C_2$	$C_3$	$C_4$	$C_5$
$A_1$	$〈0.6,(0.3,0.8)〉$	$〈0.8,(0.4,0.5)〉$	$〈0.7,(0.2,0.6)〉$	$〈0.5,(0.7,0.2)〉$	$〈0.4,(0.8,0.1)〉$
$A_2$	$〈0.7,(0.6,0.2)〉$	$〈0.8,(0.4,0.4)〉$	$〈0.4,(0.3,0.6)〉$	$〈0.6,(0.7,0.5)〉$	$〈0.3,(0.6,0.2)〉$
$A_3$	$〈0.3,(0.7,0.4)〉$	$〈0.8,(0.9,0.2)〉$	$〈0.9,(0.9,0.1)〉$	$〈0.7,(0.3,0.8)〉$	$〈0.6,(0.7,0.4)〉$
$A_4$	$〈0.8,(0.5,0.4)〉$	$〈0.6,(0.8,0.1)〉$	$〈0.8,(0.7,0.1)〉$	$〈0.6,(0.2,0.7)〉$	$〈0.7,(0.3,0.5)〉$

Table 3. PF decision matrix for expert 3.

	$C_1$	$C_2$	$C_3$	$C_4$	$C_5$
$A_1$	$〈0.3,(0.5,0.6)〉$	$〈0.8,(0.4,0.7)〉$	$〈0.4,(0.7,0.4)〉$	$〈0.4,(0.9,0.3)〉$	$〈0.6,(0.6,0.5)〉$
$A_2$	$〈0.7,(0.7,0.3)〉$	$〈0.3,(0.7,0.1)〉$	$〈0.8,(0.8,0.1)〉$	$〈0.7,(0.6,0.2)〉$	$〈0.4,(0.4,0.8)〉$
$A_3$	$〈0.6,(0.3,0.8)〉$	$〈0.7,(0.8,0.2)〉$	$〈0.6,(0.9,0.1)〉$	$〈0.6,(0.4,0.6)〉$	$〈0.7,(0.8,0.1)〉$
$A_4$	$〈0.3,(0.9,0.3)〉$	$〈0.6,(0.5,0.5)〉$	$〈0.7,(0.3,0.4)〉$	$〈0.4,(0.8,0.3)〉$	$〈0.3,(0.4,0.5)〉$

Table 4. The aggregate PF decision matrix.

	$C_1$	$C_2$	$C_3$	$C_4$	$C_5$
$A_1$	(0.533,0.637)	(0.568,0.598)	(0.672,0.209)	(0.803,0.172)	(0.787,0.189)
$A_2$	(0.638,0.315)	(0.429,0.481)	(0.737,0.289)	(0.568,0.449)	(0.537,0.350)
$A_3$	(0.562,0.527)	(0.832,0.196)	(0.837,0.238)	(0.393,0.697)	(0.797,0.206)
$A_4$	(0.779,0.310)	(0.672,0.209)	(0.496,0.256)	(0.687,0.402)	(0.511,0.534)

Table 5. The aggregate PF decision matrix under complete confidence.

	$C_1$	$C_2$	$C_3$	$C_4$	$C_5$
$A_1$	(0.466,0.676)	(0.574,0.559)	(0.680,0.204)	(0.813,0.175)	(0.810,0.171)
$A_2$	(0.624,0.287)	(0.515,0.305)	(0.635,0.361)	(0.633,0.417)	(0.542,0.331)
$A_3$	(0.596,0.469)	(0.844,0.221)	(0.880,0.141)	(0.397,0.703)	(0.808,0.214)
$A_4$	(0.767,0.327)	(0.680,0.204)	(0.580,0.202)	(0.552,0.517)	(0.437,0.507)