A Hybrid Multiobjective Differential Evolution Algorithm and Its Application to the Optimization of Grinding and Classification

Table 2

The performance results of the each algorithm on the test function.

Test function	Algorithm	𝛾	SP
ZDT2	DEMO/Parent	0.005120±0.000312	0.000630±0.000010
	NSGA-2	0.007120±0.000413	0.000540±0.000940
	SM-DEMO	0.004013±0.000230	0.000423±0.000011
ZDT3	DEMO/Parent	0.009704±0.000027	0.007512±0.000165
	NSGA-2	0.014067±0.000059	0.006540±0.000124
	SM-DEMO	0.004704±0.000003	0.004450±0.000153
ZDT4	DEMO/Parent	2.009704±0.901164	0.011031±0.001104
	NSGA-2	3.144067±2.100740	0.010122±0.000072
	SM-DEMO	0.874001±0.014323	0.008721±0.000159
ZDT6	DEMO/Parent	0.649704±0.004912	0.104520±0.015486
	NSGA-2	1.014067±0.010421	0.007942±0.000105
	SM-DEMO	0.007750±0.000083	0.002014±0.000117