A New Adaptive Hungarian Mating Scheme in Genetic Algorithms

Table 6

Comparison of results on two test problems.

Problem instance	Our method		Galán et al. [8]				Ishibuchi and Shibata [13]
	Avg	Std	Avg	Std	-test	value	Avg	Std	-test	value
berlin52	9.02e3	3.09e2	9.27e3	3.32e2	+	1.6e − 59	9.24e3	3.38e2	+	4.4e − 45
kroA100	3.51e4	1.48e3	3.81e4	1.60e3	+	3.5e − 228	3.77e4	1.41e3	+	9.2e − 213
bier127	1.87e5	6.20e3	1.96e5	6.78e3	+	1.2e − 158	1.97e5	6.46e3	+	4.4e − 188
pr152	1.76e5	1.00e4	1.96e5	1.12e4	+	1.6e − 227	2.00e5	1.07e4	+	3.5e − 290
G1000.2.5	2.54e2	8.68e0	3.01e2	3.13e1	+	5.2e − 248	3.04e2	1.15e1	+	0
G1000.20	3.95e3	2.61e1	4.09e3	9.47e1	+	1.0e − 245	4.09e3	3.21e1	+	0
U1000.05	3.71e2	2.20e1	4.96e2	8.40e1	+	9.7e − 246	5.18e2	2.64e1	+	0
U1000.40	4.14e3	2.65e2	4.99e3	5.94e2	+	5.9e − 220	5.31e3	2.23e2	+	0

CPU: Intel Xeon E5530 2.40 GHz. Average from 1,000 runs.
Avg: average (the smaller, the better); Std: standard deviation.
value: the smaller, the more significant.
+: significantly better under level 1.00e − 02.
: it means that this value is less than 1.0e − 300.