Quantum Behaved Particle Swarm Optimization Algorithm Based on Artificial Fish Swarm

Table 2

The test function optimization results.

		The optimal solution	Average value	The average operation time (seconds)	The number of successful	The success rate
	QAFSP	7	7	0.21	50	1
	QPSO	7	7.0004	0.03	45	0.9
	QGA	7	7.0009	2.07	40	0.8
	AFSA	7	7.0019	3.54	37	0.74
	QAFSP	−1	−0.99902	4.16	45	0.9
	QPSO	−1	−0.99756	0.31	35	0.7
	QGA	−1	−0.99137	5.59	19	0.38
	AFSA	−1	−0.95641	9.03	0	0
	QAFSP	−1.0316	−1.0316	0.10	50	1
	QPSO	−1.0316	−1.0315	0.02	49	0.98
	QGA	−1.0316	−0.8293	7.58	14	0.28
	AFSA	−1.0316	20.1389	11.83	12	0.24
	QAFSP	−6.5511	−6.5511	0.22	50	1
	QPSO	−6.5511	−6.5457	0.03	49	0.98
	QGA	−6.5511	−6.4807	0.95	8	0.16
	AFSA	−6.5511	−6.5502	0.23	34	0.68
	QAFSP			13.26	50	1
	QPSO	0.00012216	0.13664	0.64	6	0.12
	QGA		3.7042	18.55	4	0.08
	AFSA	0.23427	5.9101	16.87	0	0
	QAFSP		0.00021545	9.65	49	0.98
	QPSO		0.00076334	1.52	42	0.84
	QGA	0.079839	5.7882	37.15	0	0
	AFSA	13.6422	25.9938	39.69	0	0
	QAFSP			2.05	50	1
	QPSO	0.026063	0.07969	0.75	0	0
	QGA	14464.0999	27368.9906	27.81	0	0
	AFSA	1364.2993	8233.3037	17.91	0	0
	QAFSP			6.45	50	1
	QPSO	0.034844	0.1822	0.90	0	0
	QGA	3.1575	3.2964	27.93	0	0
	AFSA	9.5439	12.1968	26.76	0	0