A New Logistic Dynamic Particle Swarm Optimization Algorithm Based on Random Topology

Table 3

Comparison between random topologies with different average degrees.

Benchmark function	𝐾	Average degree	Clustering coefficient	Perform.	Prop.
Sphere	1	1.958	0.753	1.38𝐸−15	0.768507
	2	3.700	0.541	1.53𝐸−30	0.817693
	3	5.244	0.498	3.70𝐸−32	0.82624
	4	6.640	0.510	5.92𝐸−33	0.833993
	5	7.928	0.534	4.15𝐸−33	0.836973
	6	9.040	0.568	8.09𝐸−34	0.84178
	7	10.116	0.606	1.00𝐸−33	0.84702
	8	11.092	0.641	1.68𝐸−34	0.84278
	9	11.814	0.671	9.18𝐸−34	0.84446
Schaffer's F6	1	1.942	0.753	0.002915	0.497393
	2	3.700	0.545	0.001757	0.63916
	3	5.228	0.497	0.001749	0.681847
	4	6.626	0.508	0.00136	0.716053
	5	7.926	0.530	0.001943	0.6303
	6	8.998	0.563	0.003303	0.558613
	7	10.070	0.602	0.00272	0.59538
	8	11.078	0.643	0.003313	0.542707
	9	11.854	0.673	0.002915	0.558667
Rastrigin	1	1.956	0.751	63.65224	0.868587
	2	3.688	0.546	58.10571	0.923933
	3	5.198	0.500	58.64275	0.915993
	4	6.694	0.507	62.68228	0.934207
	5	7.940	0.532	58.80197	0.94144
	6	9.018	0.565	62.54299	0.93782
	7	10.118	0.608	59.10044	0.944673
	8	10.982	0.638	61.90622	0.908687
	9	11.916	0.674	63.51805	0.925493
Schwefel	1	1.956	0.752	4773.649	0.91388
	2	3.694	0.548	4366.848	0.942427
	3	5.234	0.500	4388.532	0.9436
	4	6.616	0.502	4399.952	0.943533
	5	7.922	0.532	4286.961	0.950633
	6	9.046	0.571	4397.724	0.950987
	7	10.074	0.602	4412.291	0.932327
	8	11.016	0.641	4420.19	0.951007
	9	11.734	0.667	4397.566	0.933313
Ackley	1	1.948	0.751	1.224299	0.960753
	2	3.690	0.549	1.030908	0.969733
	3	5.282	0.493	0.985613	0.972333
	4	6.672	0.507	1.256866	0.97304
	5	7.872	0.539	1.238158	0.973947
	6	9.028	0.568	1.593962	0.974087
	7	10.134	0.611	1.755415	0.97432
	8	10.922	0.640	1.919407	0.974847
	9	11.876	0.671	1.962931	0.97564