Optimizing High-Dimensional Functions with an Efficient Particle Swarm Optimization Algorithm

Table 2

The performance of PSOTS, the traditional PSO algorithm (PSO), the AsynLnPSO algorithm (APSO), the LinWPSO algorithm (LPSO), GPSO, CCAS, and VPSO on 9 functions in the benchmark dataset when the dimensionality is 150.

Function		Ackley	Cigar	Griewank	Rastrigin	Rosenbrock	Noncon-rast	Schwefel	Tablet	Ellipse
PSOTS	Best	0.425	5116.750	0.005	90.681	190.554	92.819	91.398	0.717	73.556
	Mean	0.481	6324.494	0.007	116.478	205.230	121.122	99.691	1.200	220.456
	STD	0.040	1068.823	0.001	20.753	12.054	34.780	3.756	0.336	77.121
PSO	Best	0.511	7021.059	0.008	469.011	224.680	695.866	78.957	1.479	137.010
	Mean	0.618	9136.416	0.011	546.090	255.356	872.599	89.771	1.782	250.101
	STD	0.057	1282.803	0.001	39.747	22.179	101.196	6.417	0.230	66.171
APSO	Best	0.605	7502.959	0.008	479.003	230.769	686.900	82.957	1.367	127.008
	Mean	0.679	9991.976	0.011	551.005	251.660	818.986	90.327	1.839	310.903
	STD	0.061	1541.439	0.002	48.771	14.570	81.069	5.341	0.321	93.523
LPSO	Best	0.521	5367.866	0.008	472.005	217.039	788.823	75.947	1.367	106.011
	Mean	0.598	8151.604	0.011	542.003	231.982	872.196	83.736	1.711	275.302
	STD	0.052	1557.269	0.001	56.972	10.096	56.059	4.234	0.240	91.931
GPSO	Best	0.474	6025.012	0.008	295.561	239.459	577.883	89.198	1.145	96.957
	Mean	0.577	7641.640	0.012	450.332	300.165	743.809	110.752	1.708	247.262
	STD	0.064	1539.431	0.002	67.280	14.744	74.040	5.309	0.241	80.445
CCAS	Best	0.469	5396.279	0.007	337.274	211.787	522.905	78.234	1.173	125.268
	Mean	0.534	7310.747	0.010	510.999	292.134	630.278	94.943	1.712	257.922
	STD	0.073	1607.475	0.002	99.349	17.176	89.913	6.630	0.272	88.161
VPSO	Best	0.438	5077.673	0.007	211.627	207.912	322.436	67.878	1.073	126.744
	Mean	0.490	7205.705	0.013	389.462	241.185	549.318	89.587	1.568	238.459
	STD	0.043	1766.442	0.003	83.077	17.642	80.935	7.567	0.213	74.187