Racing Sampling Based Microimmune Optimization Approach Solving Constrained Expected Value Programming

Table 1

Comparison of statistical results for Example 5.

Algor.	Max.	Min.	Mean	Std. dev.	CI	FR (%)	AR (s)
SSGA-A	0.14	0.10	0.11	0.01		80	49.5
SSGA-B	0.13	0.10	0.11	0.01		87	49.6
NIOA-A	0.25	0.16	0.21	0.03		80	27.6
NIOA-B	0.26	0.17	0.20	0.02		87	24.7
IOA	0.39	0.22	0.29	0.05		90	16.1

CI represents the confidence interval of objective values for the solutions acquired; FR stands for the rate of feasible solutions among all the gotten solutions; AR denotes the average runtime required by 30 runs.