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

Table 4

The comparison of performance.

Test function	Algorithm	𝛾	SP
CTP1	CNSGA-Π	0.021317±0.000323	0.873321±0.08725
	The proposed	0.009836±0.000410	0.567933±0.01845
CTP2	CNSGA-Π	0.011120±0.000753	0.78314±0.02843
	The proposed	0.007013±0.000554	0.296543±0.00453
BNH	CNSGA-Π	0.014947±0.000632	0.336941±0.00917
	The proposed	0.013766±0.000043	0.209321±0.00561
TNK	CNSGA-Π	0.013235±0.000740	0.464542±0.00730
	The proposed	0.006435±0.000017	0.224560±0.00159