Effective Evolutionary Algorithm for Solving the Real-Resource-Constrained Scheduling Problem

Table 9

Makespan of algorithms (in hour).

Dataset instance	GreedyDO	GA			R-CSM
		Avg	Best	Std	Avg	Best	Std
100_5_22_15	630	524	517	5	485	484	1.41
100_5_46_15	693	587	584	5	541	538	2.55
100_5_48_9	779	535	528	10	493	490	2.16
100_5_64_15	640	530	527	2	496	490	4.55
100_5_64_9	597	521	508	10	479	474	3.68
100_10_26_15	370	294	292	2	238	237	0.94
100_10_47_9	549	299	296	3	256	253	2.36
100_10_48_15	344	282	279	3	245	242	2.25
100_10_64_9	533	305	296	7	249	243	5.32
100_10_65_15	426	290	286	5	247	245	1.25
100_20_22_15	353	169	163	6	127	124	3.4
100_20_46_15	394	207	197	7	167	164	2.85
100_20_47_9	390	186	185	0	146	143	1.89
100_20_65_15	310	243	240	2	213	210	2.05
100_20_65_9	408	187	181	5	133	128	4.5
200_10_128_15	780	583	577	5	471	468	2.94
200_10_50_15	763	577	553	17	489	485	3.3
200_10_50_9	817	589	585	5	484	484	0.47
200_10_84_9	999	583	567	11	509	505	3.91
200_10_85_15	706	555	549	5	476	474	1.32
200_20_145_15	480	328	326	2	244	240	3.48
200_20_54_15	488	385	363	21	261	257	3.19
200_20_55_9	999	318	312	4	251	248	2.87
200_20_97_15	680	438	424	10	335	334	1.89
200_20_97_9	816	326	321	6	249	244	3.42
200_40_133_15	512	222	215	6	154	148	4.19
200_40_45_15	616	210	201	6	165	161	3.68
200_40_45_9	821	213	209	3	159	152	8.06
200_40_90_9	963	215	211	3	152	148	3.72
200_40_91_15	519	205	200	3	141	135	4.92