Quantum Behaved Particle Swarm Optimization Algorithm Based on Artificial Fish Swarm

Table 1

The parameters of the algorithm.

		Population scale	Maximum number of iterations	Individual test times	Individual perception of distance	Congestion factor	The maximum step size	Code length
	QAFSP	20	50	5	50	1.618	0.1	—
	QPSO	20	50	—	—	—	—	—
	QGA	100	100	—	—	—	—	20
	AFSA	100	100	5	50	11.618	1.25	—
	QAFSP	100	100	5	150	1.618	0.1	—
	QPSO	100	100	—	—	—	—	—
	QGA	150	100	—	—	—	—	20
	AFSA	150	100	5	150	11.618	1.25	—
	QAFSP	10	50	5	100	1.618	0.1	—
	QPSO	10	50	—	—	—	—	—
	QGA	200	100	—	—	—	—	20
	AFSA	200	100	10	100	11.618	1.25	—
	QAFSP	20	50	5	5	1.618	0.1	—
	QPSO	20	50	—	—	—	—	—
	QGA	50	50	—	—	—	—	20
	AFSA	20	50	5	5	11.618	1.25	—
	QAFSP	200	100	5	10	1.618	1.25	—
	QPSO	200	100	—	—	—	—	—
	QGA	200	100	—	—	—	—	20
	AFSA	200	100	20	10	11.618	11.25	—
	QAFSP	150	100	5	200	1.618	0.1	—
	QPSO	200	200	—	—	—	—	—
	QGA	200	100	—	—	—	—	20
	AFSA	200	200	50	200	61.618	21.25	—
	QAFSP	50	100	5	300	1.618	0.1	—
	QPSO	200	100	—	—	—	—	—
	QGA	200	100	—	—	—	—	5
	AFSA	200	100	20	300	61.618	21.25	—
	QAFSP	100	100	5	100	1.618	0.1	—
	QPSO	200	100	—	—	—	—	—
	QGA	200	100	—	—	—	—	5
	AFSA	200	100	20	100	11.618	11.25	—