A Multipopulation PSO Based Memetic Algorithm for Permutation Flow Shop Scheduling

Table 2

Comparisons of PSOMA and MPSOMA.

Problem	𝑛, 𝑚	𝐶	PSOMA				MPSOMA
			BRE	ARE	WRE	𝑇avg (s)	BRE	ARE	WRE	𝑇avg (s)
Car1	11, 5	7038	0	0	0	0.68	0	0	0	24.35
Car2	13, 4	7166	0	0	0	0.95	0	0	0	40.36
Car3	12, 5	7312	0	0	0	1.06	0	0	0	32.31
Car4	14, 4	8003	0	0	0	1.22	0	0	0	53.13
Car5	10, 6	7720	0	0.018	0.375	0.70	0	0	0	22.10
Car6	8, 9	8505	0	0.114	0.764	0.49	0	0	0	17.52
Car7	7, 7	6590	0	0	0	0.30	0	0	0	8.09
Car8	8, 8	8366	0	0	0	0.42	0	0	0	11.47
Rec01	20, 5	1247	0	0.144	0.160	2.60	0	0	0	240.91
Rec03	20, 5	1109	0	0.189	0.721	2.50	0	0	0	231.94
Rec05	20, 5	1242	0.242	0.242	0.242	2.39	0.242	0.242	0.242	216.64
Rec07	20, 10	1566	0	0.986	1.149	2.81	0	0	0	337.90
Rec09	20, 10	1537	0	0.691	1.041	4.23	0	0	0	329.79
Rec11	20, 10	1431	0	0.129	0.978	3.79	0	0	0	329.21
Rec13	20, 15	1930	0.259	0.893	1.502	4.64	0.104	0.891	1.192	440.11
Rec15	20, 15	1950	0.051	0.628	1.076	5.23	0.615	0.877	1.333	455.37
Rec17	20, 15	1902	0	1.330	2.155	4.67	1.419	1.719	2.103	447.49
Rec19	30, 10	2093	0.43	1.313	2.102	10.49	0.287	0.506	0.860	1.66𝑒+03
Rec21	30, 10	2017	1.438	1.596	1.636	8.41	0.992	1.393	1.438	1.69𝑒+03
Rec23	30, 10	2011	0.596	1.310	2.038	9.36	0.398	0.552	0.796	1.66𝑒+03
Rec25	30, 15	2513	0.835	2.085	3.223	12.64	0.279	1.337	1.989	2.46𝑒+03
Rec27	30, 15	2373	1.348	1.605	2.402	12.15	0.969	1.336	1.728	2.25𝑒+03
Rec29	30, 15	2287	1.442	1.888	2.492	11.31	0.235	0.969	1.547	2.17𝑒+03
Rec31	50, 10	3045	1.510	2.254	2.692	37.15	0.699	1.237	1.792	1.55𝑒+04
Rec33	50, 10	3114	0	0.645	0.835	36.07	0	0.326	0.835	1.47𝑒+04
Rec35	50, 10	3277	0	0	0	29.92	0	0	0	1.32𝑒+04
Rec37	75, 20	3045	2.101	3.537	4.039	170.2	1.696	2.450	3.827	1.98𝑒+05
Rec39	75, 20	3114	1.553	2.426	2.830	155.7	0.581	1.298	1.792	1.67𝑒+05
Rec41	75, 20	3277	2.641	3.684	4.052	164.3	1.890	2.428	2.282	1.82𝑒+05