A DE-LS Metaheuristic Algorithm for Hybrid Flow-Shop Scheduling Problem considering Multiple Requirements of Customers

Table 4

Computational results about RPD and SD.

Instances	Types	DE-LS		Without LS		Best/1		Current-to-best/1		Rand/1
		RPD	SD	RPD	SD	RPD	SD	RPD	SD	RPD	SD
1	J20-M3	0.00	0.00	0.54	0.77	0.72	1.17	0.45	1.04	0.10	0.21
2	J20-M4	0.00	0.00	1.09	1.13	1.97	1.98	0.63	0.66	0.37	0.44
3	J30-M3	0.12	0.25	2.11	3.27	2.56	4.22	1.52	2.41	1.24	2.31
4	J30-M4	0.03	0.10	0.84	1.24	2.44	3.12	0.99	1.41	0.31	0.57
5	J40-M3	0.16	0.49	1.13	2.50	3.10	6.71	1.79	3.95	1.22	2.63
6	J40-M4	0.17	0.46	1.74	3.07	2.48	4.40	0.75	1.50	0.60	1.23
7	J50-M3	0.26	0.73	0.82	2.38	1.56	4.04	0.88	2.27	0.49	1.32
8	J50-M4	0.43	1.13	1.59	3.53	3.41	7.38	1.05	2.52	0.92	2.26
9	J60-M3	0.35	1.10	1.34	4.11	2.40	7.11	0.93	3.03	1.25	3.94
10	J60-M4	0.46	1.52	1.29	3.71	4.12	10.96	2.82	8.86	2.22	5.88
11	J70-M3	0.97	3.74	2.56	8.58	4.11	13.58	2.26	7.55	3.49	11.32
12	J70-M4	0.31	1.46	2.12	7.37	4.40	15.05	2.95	10.21	2.67	9.24
13	J80-M3	0.75	3.42	2.99	13.08	4.77	20.11	2.78	12.00	4.23	17.87
14	J80-M4	0.99	4.61	2.38	8.76	3.27	12.39	2.79	10.89	3.78	14.46
15	J90-M3	0.31	1.43	0.67	3.15	1.30	5.99	0.65	3.41	1.93	8.10
16	J90-M4	0.64	3.10	2.43	9.43	4.26	15.82	3.13	11.79	5.60	20.73
17	J100-M3	0.55	2.61	1.11	5.04	2.14	9.41	1.37	7.00	3.20	14.33
18	J100-M4	0.74	4.20	2.27	10.89	3.81	18.06	2.42	11.73	3.72	17.64
Average		0.40	1.69	1.61	5.11	2.93	8.97	1.68	5.68	2.07	7.47