. 2024 Jul 19;27(8):110541. doi: 10.1016/j.isci.2024.110541

Table 1.

Solution sets with different decision preferences

Preferences	Criteria ranking^a	Weights $(w_{1}, w_{2}, w_{3}, w_{4})$	$f_{1}$ (Gt)	$f_{2}$ (trillion Yuan)	$f_{3}$ (billion person)
Low carbon preference (Pre-Lc)	$f_{4} \approx f_{1} ≻ f_{2} \approx f_{3}$	(0.499, 0.001, 0.001,0.499)	173.0	2740.7	14.8
Economic preference (Pre-Ec)	$f_{4} \approx f_{2} ≻ f_{1} \approx f_{3}$	(0.001, 0.499, 0.001, 0.499)	173.6	2750.2	14.9
Employment preference (Pre-Em)	$f_{4} \approx f_{3} ≻ f_{1} \approx f_{2}$	(0.001, 0.001, 0.499,0.499)	173.6	2750.2	14.9
Equality preference (Pre-Eq)	$f_{4} \approx f_{1} \approx f_{2} \approx f_{3}$	(0.250, 0.250, 0.250,0.250)	173.6	2750.2	14.9

Cumulative CO₂ emission (f₁), GDP (f₂), and employment (f₃) from 2018 to 2035 in low carbon preference (Pre-Lc), economic preference (Pre-Ec), employment preference (Pre-Em), and equality preference (Pre-Eq) when the cumulative dynamic input-output balance deviations (f₄) is equally important alongside the priority objective. See also Table S13 and Data S11.

$f_{1} ≻ f_{2}$ represents that $f_{1}$ is strictly more important than $f_{2}$ , while $f_{1} \approx f_{2}$ means that $f_{1}$ is as important as $f_{2}$ .