Statistical Design of Genetic Algorithms for Combinatorial Optimization Problems

Table 5

The results of the CCF design.

	Input variables				Responses
Runs	𝑋1	𝑋2	𝑋3	𝑋4	𝑌1	𝑌2
(1)	0	0	1	0	−0.02	0.38
(2)	1	0	0	0	−0.02	0.29
(3)	0	−1	0	0	−0.02	0.46
(4)	−1	0	0	0	−0.02	0.75
(5)	1	1	−1	1	−0.01	0.23
(6)	1	−1	1	−1	−0.02	0.37
(7)	−1	1	1	1	−0.02	0.57
(8)	1	−1	1	1	−0.01	0.28
(9)	0	0	0	−1	−0.02	0.48
(10)	0	1	0	0	−0.01	0.37
(11)	−1	−1	1	1	−0.02	0.73
(12)	0	0	0	0	−0.02	0.41
(13)	0	0	0	0	−0.01	0.41
(14)	1	1	1	1	−0.01	0.23
(15)	0	0	0	1	−0.01	0.36
(16)	1	1	1	−1	−0.02	0.3
(17)	−1	−1	−1	−1	−0.03	0.96
(18)	1	1	−1	−1	−0.01	0.31
(19)	0	0	0	0	−0.01	0.41
(20)	−1	1	−1	1	−0.01	0.61
(21)	−1	−1	−1	1	−0.02	0.76
(22)	−1	−1	1	−1	−0.03	0.96
(23)	1	−1	−1	−1	−0.01	0.38
(24)	−1	1	−1	−1	−0.03	0.78
(25)	1	−1	−1	1	−0.01	0.29
(26)	0	0	−1	0	−0.02	0.41
(27)	0	0	0	0	−0.02	0.42
(28)	−1	1	1	−1	−0.03	0.78