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

Table 1

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 100.

Function		Ackley	Cigar	Griewank	Rastrigin	Rosenbrock	Noncon-rast	Schwefel	Tablet	Ellipse
PSOTS	Best	0.267	1514.120	0.003	46.419	115.979	27.432	46.644	0.510	43.013
	Mean	0.365	2926.385	0.005	54.378	127.799	53.147	54.476	0.720	93.883
	STD	0.078	828.050	0.001	6.993	12.423	14.221	4.598	0.161	28.614
PSO	Best	0.329	2592.790	0.005	186.276	119.860	379.094	36.258	0.732	53.693
	Mean	0.470	3733.502	0.007	250.535	138.929	491.466	42.399	1.033	89.141
	STD	0.068	664.997	0.002	32.151	10.426	82.755	4.212	0.169	24.346
APSO	Best	0.411	3565.981	0.006	175.738	133.197	413.469	35.950	0.902	65.058
	Mean	0.478	4494.736	0.007	241.698	143.726	497.665	44.798	1.137	104.126
	STD	0.040	679.345	0.001	44.640	7.900	72.039	4.644	0.238	26.315
LPSO	Best	0.333	2522.980	0.005	161.634	127.660	385.249	35.380	0.798	73.928
	Mean	0.449	3742.696	0.007	252.637	138.899	467.999	43.031	1.131	107.747
	STD	0.070	1030.457	0.001	43.480	9.272	67.804	5.211	0.194	29.712
GPSO	Best	0.312	2221.012	0.005	121.513	131.571	227.312	44.372	0.735	55.721
	Mean	0.427	3251.760	0.008	203.624	168.632	359.351	53.921	1.129	95.463
	STD	0.071	943.279	0.002	41.531	11.212	65.231	5.137	0.134	23.461
CCAS	Best	0.308	2013.537	0.004	124.249	121.326	195.272	42.681	0.683	52.381
	Mean	0.392	3121.583	0.007	227.515	173.625	293.422	51.732	1.127	91.272
	STD	0.068	856.863	0.001	52.234	10.521	74.321	4.928	0.183	25.641
VPSO	Best	0.281	1923.361	0.004	93.627	126.731	143.368	33.291	0.654	49.728
	Mean	0.353	3251.672	0.008	182.676	165.472	252.431	43.562	0.972	88.362
	STD	0.042	943.612	0.002	45.572	9.837	78.635	5.138	0.136	26.732