Energy Saving in Flow-Shop Scheduling Management: An Improved Multiobjective Model Based on Grey Wolf Optimization Algorithm

Table 4

Comparison of algorithm running results’ SP.

SP		Kursawe	Schaffer	Viennet2	Viennet3	ZDT1	ZDT6
KMGWO	Min	1.869705	0.464979	0.229326	1.681636	0.057698	0.170041
	Max	2.140332	0.628268	0.354561	2.394785	0.067846	0.255117
	Mean	2.005019	0.546624	0.291944	2.038211	0.062772	0.212579
	Std	0.191362	0.115463	0.088554	0.504272	0.007176	0.060158
MOGWO	Min	2.071943	0.544736	0.338835	1.691569	0.058589	0.082575
	Max	2.255649	0.588034	0.395661	2.20073	0.061941	0.180822
	Mean	2.163796	0.566385	0.367248	1.946149	0.060265	0.131699
	Std	0.129899	0.030616	0.040182	0.360031	0.00237	0.069471
MOPSO	Min	1.812654	0.597622	0.406334	2.205442	0.074537	0.309447
	Max	1.948818	0.601261	0.41442	2.221322	0.076896	0.435343
	Mean	1.880736	0.599441	0.410377	2.213382	0.075716	0.372395
	Std	0.096282	0.002573	0.005718	0.011228	0.001668	0.089021
NSGA2	Min	1.442097	1.198419	0.225471	2.55751	0.342942	0.245284
	Max	1.490551	1.228526	0.2299	2.645984	0.343657	0.372529
	Mean	1.466324	1.213472	0.227685	2.601747	0.343299	0.308907
	Std	0.034262	0.021289	0.003132	0.06256	0.000505	0.089976
MOEA/D	Min	1.645038	0.234028	0.238373	0.097528	0.054964	0.072255
	Max	1.655435	0.295418	0.312842	0.145355	0.063264	0.15472
	Mean	1.650237	0.264723	0.275607	0.121441	0.059114	0.113488
	Std	0.007352	0.04341	0.052658	0.033819	0.005869	0.058311
PESA2	Min	2.091793	0.599484	0.276225	2.362664	0.069884	0.22178
	Max	2.160544	0.638922	0.34284	2.398225	0.076021	0.814949
	Mean	2.126169	0.619203	0.309533	2.380444	0.072953	0.518364
	Std	0.048614	0.027887	0.047104	0.025145	0.00434	0.419434