A Many-Objective Optimization Algorithm Based on Weight Vector Adjustment

Table 7

Summary of statistical test results in Table 4.

NSGA-III-WA	Objective number	vs. NSGA-III	vs. VAEA	vs. RVEA	vs. MOEA/D	vs. MOEA/D-M2M
GD	3	+: 6, =: 0, −: 0	+: 6, =: 0, −: 0	+: 6, =: 0, −: 0	+: 6, =: 0, −: 0	+: 5, =: 0, −: 1
	5	+: 5, =: 0, −: 1	+: 6, =: 0, −: 0	+: 6, =: 0, −: 0	+: 5, =: 1, −: 0	+: 5, =: 0, −: 1
	8	+: 5, =: 0, −: 1	+: 6, =: 0, −: 0	+: 5, =: 1, −: 0	+: 6, =: 0, −: 0	+: 5, =: 1, −: 0
	10	+: 5, =: 0, −: 1	+: 5, =: 0, −: 1	+: 5, =: 1, −: 0	+: 6, =: 0, −: 0	+: 5, =: 0, −: 1
	15	+: 5, =: 0, −: 1	+: 5, =: 0, −: 1	+: 6, =: 0, −: 0	+: 6, =: 0, −: 0	+: 6, =: 0, −: 0

Note: “+,” “=,” and “−” represent wins, equal to, and lose.