Optimizing Product Configuration Problems with Multisourcing Supplier Selections under Both Carbon Cap and Carbon Tax Regulations

Table 6

Computational results.

Case ID	Two-stage algorithm			Classical GA			gPSO
I-J-L-K	Best (e06)	Avg (e06)	CPU time	Best (e06)	Avg (e06)	CPU time	Best (e06)	Avg (e06)	CPU time
5-15-3-3	8.72	8.74	0.54	8.63	8.65	1.12	8.80	8.80	0.78
5-15-5-5	6.69	6.69	1.71	6.68	6.69	2.06	6.83	6.85	1.90
5-15-10-10	5.71	5.71	5.07	5.87	5.90	3.73	5.92	5.94	4.55
10-30-3-5	27.45	27.53	2.73	26.99	27.04	3.32	28.13	28.16	1.84
10-30-5-10	26.13	26.15	7.93	26.37	26.37	5.77	26.84	26.89	4.83
10-30-10-15	27.76	27.78	11.39	28.62	28.64	14.50	28.77	28.88	33.79
20-50-3-10	101.30	101.41	10.59	101.48	101.48	10.20	102.11	102.33	5.85
20-50-5-15	91.58	91.66	25.87	92.61	92.73	55.02	93.36	93.46	25.30
20-50-10-20	85.83	85.91	173.87	87.95	88.04	209.51	88.40	88.54	104.41
30-70-3-15	223.29	223.41	22.46	223.81	224.05	51.40	226.34	226.51	18.38
30-70-5-20	203.02	203.14	112.18	205.10	205.24	128.29	210.37	210.84	58.53
30-70-10-25	196.70	196.78	221.72	199.59	199.91	303.42	200.29	200.37	233.58
50-100-3-20	482.37	476.46	82.99	485.09	485.44	119.59	490.74	491.31	47.76
50-100-5-25	457.46	468.60	185.27	490.48	490.86	235.10	501.15	502.79	139.37
50-100-10-30	484.12	487.45	478.76	500.39	500.55	601.37	521.55	523.76	529.79