Computational Intelligence and Neuroscience

Research Article

An Improved Real-Coded Genetic Algorithm Using the Heuristical Normal Distribution and Direction-Based Crossover

Table 2

The computational results of various algorithms.


Function	IRCGA-1		IRCGA-2		IRCGA-3		SPXMOGA		HGA		MOIRCGA
Function	t_ave (s)	iter_ave (times)	t_ave (s)	iter_ave (times)	t_ave (s)	iter_ave (times)	t_ave (s)	iter_ave (times)	t_ave (s)	iter_ave (times)	t_ave (s)	iter_ave (times)

f₁	0.1142	89.6250	0.0709	68.1900	0.0679	51.3940	0.2024	624.2430	0.0168	17.1530	0.0155	6.2150
f₂	0.0285	18.2660	0.0108	11.9562	0.0064	5.6540	0.0389	15.8500	0.0041	3.7000	0.0020	2.0330
f₃	0.0842	36.2200	0.0095	13.6253	0.0120	15.7290	0.0824	20.5700	0.0068	4.8800	0.0063	3.1400
f₄	0.0648	22.7620	0.0072	10.6824	0.0088	12.6810	0.1223	275.3800	0.0135	8.4500	0.0046	3.5120
f₅	0.0664	26.5900	0.0186	36.2560	0.0190	38.2210	0.1317	428.9000	0.0179	23.6320	0.0158	20.8310
f₆	0.0260	15.7500	0.0156	20.2610	0.0141	18.6410	0.0271	82.4800	0.0601	26.0600	0.0068	4.9460
f₇	0.1305	41.1900	0.1356	242.6236	0.1287	224.1050	0.1936	263.3200	0.0862	36.6340	0.0198	22.6480
f₈	0.2868	185.0700	0.2568	263.6246	0.2107	451.7110	0.6230	1785.6240	0.1962	156.2300	0.1138	127.0690
f₉	0.1758	59.6400	0.0546	80.6528	0.0357	60.8970	0.1989	96.7800	0.0265	16.5600	0.0120	12.7330
f₁₀	16.5687	11835.8600	30.6528	31042.6540	27.3205	28412.8500	35.6283	32461.6280	15.7377	10983.8614	13.2385	8414.4000
f₁₁	0.0217	25.8100	0.0156	32.6246	0.0138	28.1210	0.1867	42.8300	0.0138	8.5320	0.0064	6.9180
f₁₂	0.0696	50.5600	0.0653	86.6810	0.0350	56.0080	0.2302	127.5760	0.0283	21.6230	0.0194	19.5300
f₁₃	0.1734	58.6100	0.0236	26.0625	0.0168	11.0350	0.1926	72.9426	0.0156	9.6230	0.0147	7.8780
f₁₄	0.1431	46.7300	0.0316	65.2681	0.0287	49.7220	0.2136	98.9260	0.0289	33.2310	0.0266	31.3050
f₁₅	0.1072	34.0400	0.1562	226.3584	0.1037	180.7190	1.8626	236.2580	0.0626	28.5300	0.0221	24.9230
f₁₆	1.6890	1013.5681	1.7869	1926.5863	1.6216	1711.9600	6.5681	4267.8320	1.0321	1201.6560	0.8660	813.0560