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

Table 4

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 300.

Function		Ackley	Cigar	Griewank	Rastrigin	Rosenbrock	Noncon-rast	Schwefel	Tablet	Ellipse
PSOTS	Best	0.480	11239.310	0.007	270.220	435.735	243.118	236.858	1.757	768.211
	Mean	0.551	16700.500	0.010	304.659	460.780	309.250	245.861	2.642	1044.533
	STD	0.052	2864.634	0.002	25.149	20.493	40.135	8.772	0.626	199.579
PSO	Best	0.725	26182.680	0.016	797.438	558.017	1958.180	218.271	3.607	1087.085
	Mean	0.837	29781.450	0.017	1558.475	581.011	2144.747	230.463	4.063	1383.916
	STD	0.071	3263.52	0.002	277.037	19.795	93.044	9.453	0.347	199.579
APSO	Best	0.792	26675.420	0.015	506.867	569.283	622.970	225.835	3.506	1164.937
	Mean	0.872	30096.930	0.019	1530.612	604.836	2103.667	234.035	4.481	1444.022
	STD	0.054	2666.445	0.002	363.651	23.546	527.097	3.823	0.511	196.814
LPSO	Best	0.676	21480.700	0.014	499.562	510.421	1961.123	210.576	3.263	1058.076
	Mean	0.751	24369.240	0.017	1575.189	559.471	2243.721	223.646	4.070	1214.656
	STD	0.053	2254.595	0.002	454.681	33.480	167.328	9.551	0.558	105.178
GPSO	Best	0.610	14351.613	0.013	386.601	578.391	290.975	248.015	2.805	837.559
	Mean	0.730	21013.471	0.020	1204.562	702.838	735.345	276.637	4.017	1290.958
	STD	0.083	2958.214	0.002	295.832	24.869	83.056	9.544	0.529	188.628
CCAS	Best	0.564	13233.792	0.011	566.908	512.184	179.650	215.826	2.632	941.745
	Mean	0.690	21699.961	0.016	1365.832	671.090	721.552	242.225	3.930	1207.535
	STD	0.103	2854.312	0.003	121.696	27.090	193.967	8.806	0.481	173.677
VPSO	Best	0.574	13157.77	0.014	550.812	507.583	164.3968	180.937	2.272	888.696
	Mean	0.652	20398.05	0.019	1024.967	578.245	677.9356	234.522	3.389	1159.823
	STD	0.042	2905.144	0.004	181.691	21.837	189.815	5.169	0.557	220.522