Improvement Analysis and Application of Real-Coded Genetic Algorithm for Solving Constrained Optimization Problems

Table 2

The computational results of five ICRGAs.

function	Algorithm	Average running time (s)	Average number of iterations (times)	The average value of population diversity when converging to the optimal solution
f1	IRCGA-1	0.6397	205.3840	28.6652
	IRCGA-2	0.0209	24.1420	50.2294
	IRCGA-3	0.0253	30.2560	30.6849
	IRCGA-4	0.6936	233.2300	11.2693
	IRCGA-5	0.5863	196.5600	27.2.46
f2	IRCGA-1	0.4193	115.0780	5.9865
	IRCGA-2	0.0133	13.0770	10.2328
	IRCGA-3	0.0265	25.6320	6.9731
	IRCGA-4	0.6255	206.9300	1.7962
	IRCGA-5	0.0493	85.4500	7.3493
f3	IRCGA-1	0.0643	18.9930	3.4109
	IRCGA-2	0.0144	14.3210	5.8449
	IRCGA-3	0.0273	16.2350	4.7633
	IRCGA-4	0.1313	54.7800	1.4526
	IRCGA-5	0.0317	21.5400	2.8277
f4	IRCGA-1	15.7263	4630.9300	3.2163
	IRCGA-2	0.2275	219.1660	11.0648
	IRCGA-3	0.2510	272.0670	3.4109
	IRCGA-4	13.1359	4413.9000	2.0108
	IRCGA-5	0.8392	1264.6400	4.4617
f5	IRCGA-1	0.1137	36.1090	3.9642
	IRCGA-2	0.0316	30.9790	6.2602
	IRCGA-3	0.0405	32.5230	4.0683
	IRCGA-4	0.4617	157.1000	2.1785
	IRCGA-5	0.1300	145.4000	3.5308
f6	IRCGA-1	0.0547	22.0830	3.6838
	IRCGA-2	0.0208	19.6450	5.2457
	IRCGA-3	0.0312	21.0560	4.0133
	IRCGA-4	0.1831	309.6000	2.1494
	IRCGA-5	0.1280	245.7800	3.4931
f7	IRCGA-1	0.0574	18.3590	5.8063
	IRCGA-2	0.0200	15.4550	10.0381
	IRCGA-3	0.0320	16.4680	7.8151
	IRCGA-4	0.0479	26.2000	5.1667
	IRCGA-5	0.0368	29.5020	6.4071
f8	IRCGA-1	0.1381	42.6790	78.8050
	IRCGA-2	0.0262	27.7540	127.9265
	IRCGA-3	0.0328	31.2600	86.3403
	IRCGA-4	0.1464	46.9900	75.9938
	IRCGA-5	0.1458	48.5800	74.1084
f9	IRCGA-1	0.1959	60.9510	7.2904
	IRCGA-2	0.0157	16.3440	13.5928
	IRCGA-3	0.0320	21.2640	10.6016
	IRCGA-4	0.0560	26.7850	4.2582
	IRCGA-5	0.0396	23.5600	7.5200