Corrigendum to “A Novel MILP Model for the Production, Lot Sizing, and Scheduling of Automotive Plastic Components on Parallel Flexible Injection Machines with Setup Common Operators”

Table 11

Experimental results for the MILP model for lot-sizing and scheduling on parallel flexible injection machines with setup common operators.

Dataset						Number of constraints	Number of variables	Number of binary variables	Number of integer variables	Number of continuous variables	Number of nonzeros	Objective value	GAP (%)	Termination condition	Time (sec)
S1	2	4	6	2	3	392	228	96	96	36	880	30700299.29	0.00	Optimal	0.015592575
S2	4	6	8	2	3	904	504	288	288	-72	2224	9700768.824	0.00	Optimal	0.015617609
S3	6	8	16	2	3	1760	1008	576	576	-144	4736	23501097.9	0.00	Optimal	0.062484741
S4	8	10	22	2	3	2800	1596	960	960	-324	7860	18901770.98	0.00	Optimal	0.031243086
M1	10	12	24	4	14	36744	17136	13440	13440	-9744	100032	67810309.09	0.00	Optimal	12.21586823
M2	12	14	28	4	14	50596	23520	18816	18816	-14112	138992	99214112.49	0.00	Optimal	26.69681978
M3	14	16	32	4	14	66656	30912	25088	25088	-19264	184320	143015128.2	0.00	Optimal	14.35598087
M4	16	18	36	4	14	84924	39312	32256	32256	-25200	236016	146316474	0.00	Optimal	79.8799355
L1	18	20	40	6	14	156200	68880	60480	60480	-52080	432320	211521532.7	0.00	Optimal	241.9122446
L2	20	40	60	8	14	454244	195440	179200	179200	-162960	1212080	867861481	1.54	maxTimeLimit	18015.20472
L3	25	45	70	12	14	950246	399630	378000	378000	-356370	2545660	915900800.2	5.39	maxTimeLimit	18021.99296
L4	30	60	120	15	14	1893720	791280	756000	756000	-720720	5256960	1359169510	4.31	maxTimeLimit	18065.29413