A Two-Level Metaheuristic for the Job-Shop Scheduling Problem with Multipurpose Machines

Table 1

Results on Edata.

Instance	n, m	BKS	Best of TS [9]	Best of PSO [10]	Best of CP [20]	MPM-UPLA
						Best	Avg	No of Iters	Time
M6	6, 6	55	57	55	55	55	55.0	1	< 1 sec.
M10	10, 10	871	917	892	877	873	875.0	1000	0:26:10
M20	20, 5	1088	1109	1116	1088	1090	1090.2	1000	0:31:11
LA1	10, 5	609	611	609	609	609	609.0	1	< 1 sec.
LA2	10, 5	655	655	655	655	655	655.0	3	< 1 sec.
LA3	10, 5	550	573	567	567	550	550.0	89	0:00:19
LA4	10, 5	568	578	582	568	568	568.0	25	0:00:05
LA5	10, 5	503	503	503	503	503	503.0	1	< 1 sec.
LA6	15, 5	833	833	833	833	833	833.0	1	< 1 sec.
LA7	15, 5	762	765	765	765	762	762.0	377	0:04:02
LA8	15, 5	845	845	845	845	845	845.0	3	0:00:01
LA9	15, 5	878	878	878	878	878	878.0	1	< 1 sec.
LA10	15, 5	866	866	866	866	866	866.0	1	< 1 sec.
LA11	20, 5	1103	1106	1103	1106	1103	1103.0	246	0:05:09
LA12	20, 5	960	960	960	960	960	960.0	1	0:00:02
LA13	20, 5	1053	1053	1053	1053	1053	1053.0	1	0:00:01
LA14	20, 5	1123	1151	1123	1123	1123	1123.0	2	0:00:02
LA15	20, 5	1111	1111	1111	1111	1111	1111.0	2	0:00:03
LA16	10, 10	892	924	893	904	892	892.0	4	0:00:07
LA17	10, 10	707	757	707	707	707	707.0	3	0:00:04
LA18	10, 10	842	864	847	843	842	842.0	250	0:06:00
LA19	10, 10	796	850	820	799	796	796.0	161	0:04:20
LA20	10, 10	857	919	859	857	857	857.0	6	0:00:11
LA21	15, 10	1009	1066	1057	1044	1021	1025.0	1000	1:42:08
LA22	15, 10	880	919	912	887	882	883.2	1000	1:39:29
LA23	15, 10	950	980	994	950	950	950.0	68	0:06:38
LA24	15, 10	908	952	939	913	909	909.2	1000	1:39:33
LA25	15, 10	936	970	974	955	945	945.2	1000	1:31:55
LA26	20, 10	1106	1169	1173	1143	1115	1123.0	543	2:30:09
LA27	20, 10	1181	1230	1247	1188	1182	1188.8	552	2:30:12
LA28	20, 10	1142	1204	1195	1153	1149	1149.0	566	2:30:08
LA29	20, 10	1107	1210	1175	1128	1124	1130.2	555	2:30:08
LA30	20, 10	(1193)	1253	1262	1241	1220	1223.4	551	2:30:19
LA31	30, 10	(1532)	1596	1620	1552	1541	1541.0	195	2:30:31
LA32	30, 10	1698	1769	1743	1698	1698	1698.0	2	0:01:19
LA33	30, 10	1547	1575	1578	1560	1547	1547.0	2	0:01:22
LA34	30, 10	1599	1627	1662	1609	1608	1608.8	259	2:30:09
LA35	30, 10	1736	1736	1736	1736	1736	1736.0	1	0:01:06
LA36	15, 15	1160	1247	1202	1160	1160	1161.8	307	1:49:22
LA37	15, 15	1397	1453	1425	1397	1397	1397.0	41	0:11:14
LA38	15, 15	1141	1185	1209	1146	1143	1148.2	424	2:30:18
LA39	15, 15	1184	1226	1220	1184	1186	1187.4	423	2:30:14
LA40	15, 15	1144	1214	1197	1174	1150	1153.6	391	2:30:05
ABZ5	10, 10	1167	N/A	N/A	1176	1167	1167.0	235	0:06:08
ABZ6	10, 10	925	N/A	N/A	925	925	925.0	35	0:00:49
ABZ7	20, 15	(610)	N/A	N/A	638	619	621.0	150	2:30:44
ABZ8	20, 15	(637)	N/A	N/A	654	648	650.0	152	2:30:37
ABZ9	20, 15	644	N/A	N/A	668	655	656.6	155	2:30:26
CAR1	11, 5	6176	N/A	N/A	6176	6176	6182.0	723	0:03:37
CAR2	13, 4	6327	N/A	N/A	6455	6432	6433.6	1000	0:05:05
CAR3	12, 5	6856	N/A	N/A	6856	6856	6875.8	780	0:04:25
CAR4	14, 4	7789	N/A	N/A	7789	7789	7789.0	1	< 1 sec.
CAR5	10, 6	7229	N/A	N/A	7229	7229	7229.0	41	0:00:15
CAR6	8, 9	7990	N/A	N/A	8478	7990	7990.0	62	0:00:33
CAR7	7, 7	6123	N/A	N/A	6123	6123	6123.0	6	0:00:01
CAR8	8, 8	7689	N/A	N/A	7689	7689	7689.0	9	0:00:04
ORB1	10, 10	977	N/A	N/A	988	977	977.0	223	0:06:25
ORB2	10, 10	865	N/A	N/A	870	865	865.0	53	0:01:21
ORB3	10, 10	951	N/A	N/A	960	952	952.0	1000	0:26:46
ORB4	10, 10	984	N/A	N/A	1016	984	984.0	255	0:06:47
ORB5	10, 10	842	N/A	N/A	865	842	842.0	215	0:05:27
ORB6	10, 10	958	N/A	N/A	1004	958	958.0	93	0:02:48
ORB7	10, 10	387	N/A	N/A	387	389	389.0	1000	0:26:27
ORB8	10, 10	894	N/A	N/A	894	894	894.0	15	0:00:23
ORB9	10, 10	933	N/A	N/A	933	933	933.0	121	0:03:14
ORB10	10, 10	933	N/A	N/A	937	933	933.0	226	0:06:02