A synergetic combination of small and large neighborhood schemes in developing an effective procedure for solving the job shop scheduling problem

Amirghasemi, Mehrdad; Zamani, Reza

doi:10.1186/2193-1801-3-193

SpringerPlus

Table 2 Comparing the performance of the SLENP with that of TSSA

From: A synergetic combination of small and large neighborhood schemes in developing an effective procedure for solving the job shop scheduling problem

				SLENP					TSSA
Instance	Size	LB	BKS	Best	%DEV _best	T _best	Avg	T_avg(s)	Best	%DEV _best	Avg	T _avg
ft06	6 × 6	55	55	55	0.000	0	55	0.005	–	–	–	–
ft10	10 × 10	930	930	930	0.000	0.455	930	9.224	930	0.000	930	3.8
ft20	20 × 5	1165	1165	1165	0.000	0.48	1165	2.727	–	–	–	–
la19	10 × 10	842	842	842	0.000	0.13	842	0.776	842	0.000	842	0.5
la21	15 × 10	1046	1046	1046	0.000	5.3	1046.7	15.216	1046	0.000	1046	15.2
la24	15 × 10	935	935	935	0.000	10.29	936.5	20.360	935	0.000	936.2	19.8
la25	20 × 10	977	977	977	0.000	6.2	977	13.699	977	0.000	977.1	13.8
la27	20 × 10	1235	1235	1235	0.000	9.08	1235	31.980	1235	0.000	1235	11.7
la29	20 × 10	1152	1152	1162	0.868	86.64	1163.5	40.024	1153	0.087	1159.2	63.9
la36	15 × 15	1268	1268	1268	0.000	3.4	1268.3	12.937	1268	0.000	1268	9.9
la37	15 × 15	1397	1397	1397	0.000	1.97	1397	9.181	1397	0.000	1402.5	42.1
la38	15 × 15	1196	1196	1196	0.000	4.35	1198.6	14.836	1196	0.000	1199.6	47.8
la39	15 × 15	1233	1233	1233	0.000	1.31	1233.6	19.099	1233	0.000	1233.8	28.6
la40	15 × 15	1222	1222	1224	0.164	6.57	1226.6	15.926	1224	0.164	1224.5	52.1
abz5	10 × 10	1234	1234	1234	0.000	0.58	1234	3.545	–	–	–	–
abz6	10 × 10	943	943	943	0.000	0.12	943	0.151	–	–	–	–
abz7	20 × 15	656	656	662	0.915	39.04	664	64.822	658	0.305	661.8	85.9
abz8	20 × 15	645	665	668	0.451	106.52	672.4	55.935	667	0.301	670.3	90.7
abz9	20 × 15	661	678	688	1.475	98.7	689.5	35.820	678	0.000	684.8	90.2
orb01	10×10	1059	1059	1059	0.000	0.7	1059.6	5.961	1059	0.000	1059	3.5
orb02	10×10	888	888	888	0.000	0.14	888	0.475	888	0.000	888.1	6.4
orb03	10×10	1005	1005	1005	0.000	0.365	1005	7.415	1005	0.000	1012.5	13.8
orb04	10×10	1005	1005	1005	0.000	0.155	1006.2	7.580	1005	0.000	1008.3	14.3
orb05	10×10	887	887	887	0.000	1.23	887	12.093	887	0.000	888.6	6.6
orb06	10×10	1010	1010	1010	0.000	0.23	1010.9	9.165	1010	0.000	1010	8.5
orb07	10×10	397	397	397	0.000	0.14	397	0.284	397	0.000	397	0.5
orb08	10×10	899	899	899	0.000	2.26	899	6.020	899	0.000	902.5	7.2
orb09	10×10	934	934	934	0.000	0.18	934	0.509	934	0.000	934	0.4
orb10	10×10	944	944	944	0.000	0.15	944	0.176	944	0.000	944	0.3
yn1	20×20	826	884	892	0.905	66.63	897.7	40.040	884	0.000	891.3	106.3
yn2	20×20	861	907	911	0.441	1.78	913.4	62.312	907	0.000	911.2	110.4
yn3	20×20	827	892	900	0.897	59.85	903.1	42.178	892	0.000	895.5	110.8
yn4	20×20	918	968	982	1.446	49.81	986.8	56.047	969	0.103	972.6	108.7
swv01	20×10	1407	1407	1437	2.132	115.33	1458.5	60.642	1412	0.355	1423.7	142.1
swv02	20×10	1475	1475	1505	2.034	92.27	1520	64.431	1475	0.000	1480.3	119.7
swv03	20×10	1369	1398	1426	2.003	82.68	1434	48.665	1398	0.000	1417.5	139.1
swv04	20×10	1450	1470	1511	2.789	66.47	1517.8	57.664	1470	0.000	1483.7	143.9
swv05	20×10	1424	1424	1475	3.581	45.461	1492.3	58.092	1425	0.070	1443.8	146.7
swv06	20×15	1591	1678	1730	3.099	43.94	1738.2	81.892	1679	0.060	1700.1	192.5
swv07	20×15	1446	1600	1632	2.000	88.79	1648	68.546	1603	0.188	1631.3	190.2
swv08	20×15	1640	1756	1807	2.904	147.39	1814.1	71.765	1756	0.000	1786.9	190
swv09	20×15	1604	1661	1701	2.408	126.12	1707.5	68.661	1661	0.000	1689.2	193.8
swv10	20×15	1631	1754	1812	3.307	122.66	1820.6	85.666	1754	0.000	1783.7	184.6

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