Understanding Population Dynamics in Multi- and Many-Objective Evolutionary Algorithms for High-Resolution Approximations

Table 3

Algorithm comparison by accumulated PO solutions (APOS, feature) and hypervolume (HV, performance metric).

Algorithm	M		Measured		Rank
			APOS	HV	APOS	HV
NSGA-II	3	50	105.93	0.373968	3	3
			121.97	0.374248	1	1
			90.37	0.372361	4	4
MOEA/D			114.00	0.374201	2	1
NSGA-II		100	137.97	0.375304	2	3
			141.700	0.375287	1	1
			123.70	0.373812	4	4
MOEA/D			135.50	0.375422	3	1
NSGA-II		200	148.03	0.375640	1	3
			148.67	0.375904	1	1
			136.57	0.375140	4	4
MOEA/D			144.67	0.375757	3	1
NSGA-II	4	50	166.80	0.194207	4	3
			346.77	0.196897	2	2
			195.50	0.191004	3	4
MOEA/D			436.10	0.197264	1	1
NSGA-II		100	343.23	0.197154	3	3
			581.77	0.198445	2	1
			302.40	0.193841	4	4
MOEA/D			656.27	0.198507	1	1
NSGA-II		200	608.87	0.198481	3	3
			863.77	0.199031	1	1
			468.10	0.197055	4	4
MOEA/D			857.50	0.199034	1	1
NSGA-II	5	50	157.80	0.146900	4	3
			526.10	0.153434	2	2
			190.17	0.139987	3	4
MOEA/D			904.10	0.154429	1	1
NSGA-II		100	341.60	0.151905	3	3
			986.43	0.156632	2	2
			329.70	0.145065	3	4
MOEA/D			1479.13	0.157620	1	1
NSGA-II		200	718.50	0.155398	3	3
			1631.47	0.158275	2	2
			602.30	0.150032	4	4
MOEA/D			2219.17	0.159051	1	1