Solving Constrained Global Optimization Problems by Using Hybrid Evolutionary Computing and Artificial Life Approaches

Table 10

Results of t-test for TPs 5–13.

TP number	GA-3 versus AIA-2	GA-3 versus RGA-PSO	GA-3 versus AIA-PSO	AIA-2 versus RGA-PSO	AIA-2 versus AIA-PSO	RGA-PSO versus AIA-PSO
5	0.000*	0.000*	0.000*	0.485	0.163	0.002*
6	0.112	0.000*	0.000*	0.000*	0.000*	0.682
7	0.000*	0.000*	0.000*	0.000*	0.000*	0.358
8	0.000*	0.000*	0.000*	0.000*	0.000*	0.291
9	0.000*	0.000*	0.000*	0.516	0.814	0.577
10	0.000*	0.000*	0.000*	0.009*	0.001*	0.001*
11	0.000*	0.000*	0.000*	0.069	0.013*	0.884
12	0.049*	0.389	0.178	0.000*	0.007*	0.014*
13	0.003*	0.001*	0.000*	0.240	0.000*	0.019*

∗Represents that the mean values obtained using two algorithms are statistically different.)