[Retracted] An Improved Differential Evolution Solution for Software Project Scheduling Problem

Table 4

Comparison between the IDE, DE, and the PSO algorithms for SPSP.

Group	Instance	Algorithms	Success rate	Simulation time	Optimum cost	Optimum fitness
TM1		IDE-SPSP	100	15.0592	1000	0.2098
		DE	100	15.0916	1000	0.2754
		PSO	93	15.1110	1000	0.2948
		IDE-SPSP	100	15.3473	1150	0.2967
		DE	92	15.8333	1150	0.3013
		PSO	88	16.0576	1153	0.3514
		IDE-SPSP	100	16.1923	1200	0.3523
		DE	92	16.1929	1200	0.3892
		PSO	90	16.2166	1225	0.3897
		IDE-SPSP	100	16.3868	1350	0.4093
		DE	98	16.6331	1362	0.4144
		PSO	92	17.1172	1365	0.4225
		IDE-SPSP	100	17.4342	1600	0.4330
		DE	91	17.4616	1600	0.4483
		PSO	90	17.6682	1612	0.4514
		IDE-SPSP	100	17.7388	2200	0.4626
		DE	93	17.9159	2200	0.4708
		PSO	90	18.6228	2209	0.4968
		IDE-SPSP	100	18.6411	2450	0.5361
		DE	94	18.6926	2556	0.5406
		PSO	89	19.4292	2562	0.5411
		IDE-SPSP	100	19.5726	2600	0.5489
		DE	94	19.7516	2612	0.5547
		PSO	89	19.8790	2625	0.5734
		IDE-SPSP	100	19.9284	2800	0.6159
		DE	93	20.3478	2800	0.6191
		PSO	91	20.3619	2805	0.6231
		IDE-SPSP	100	20.5014	3000	0.6268
		DE	92	20.5309	3005	0.6300
		PSO	88	20.6128	3009	0.6659