A Convergent Differential Evolution Algorithm with Hidden Adaptation Selection for Engineering Optimization

Table 2

The best and mean values achieved via SaCDEhaS and SaDE algorithms.

Pro.	Alg.	FEs = 5𝐸4		FEs = 1𝐸5		FEs = 1.5𝐸5
		Best	Mean	Best	Mean	Best	Mean
T01	SaDE	0.0000𝐸+00	1.1995𝐸+01	0.0000𝐸+00	1.1995𝐸+01	0.0000𝐸+00^∗	1.1995𝐸+01
	SaCDEhaS	0.0000𝐸+00	9.4453𝐸+00	0.0000𝐸+00	9.4453𝐸+00	0.0000𝐸+00^∗	9.4453𝐸+00
T02	SaDE	−2.5473𝐸+01	−1.7971𝐸+01	−2.8422𝐸+01	−2.4597𝐸+01	−2.8423𝐸+01^∗	−2.5210𝐸+01
	SaCDEhaS	−2.6199𝐸+01	−1.8424𝐸+01	−2.8371𝐸+01	−2.4879𝐸+01	−2.8423𝐸+01^∗	−2.6207𝐸+01
T03	SaDE	1.1515𝐸−05	1.1515𝐸−05	1.1515𝐸−05	1.1515𝐸−05	1.1515𝐸−05^∗	1.1515𝐸−05
	SaCDEhaS	1.1515𝐸−05	1.1515𝐸−05	1.1515𝐸−05	1.1515𝐸−05	1.1515𝐸−05^∗	1.1515𝐸−05
T04	SaDE	1.4750𝐸+01	2.0686𝐸+01	1.4750𝐸+01	2.0686𝐸+01	1.4750𝐸+01	2.0686𝐸+01
	SaCDEhaS	1.3815𝐸+01	1.6805𝐸+01	1.3771𝐸+01	1.4971𝐸+01	1.3771𝐸+01^∗	1.4562𝐸+01
T05	SaDE	−2.9655𝐸+01	−2.4186𝐸+01	−3.2728𝐸+01	−2.7236𝐸+01	−3.3879𝐸+01	−2.9448𝐸+01
	SaCDEhaS	−3.0337𝐸+01	−2.4001𝐸+01	−3.5503𝐸+01	−2.8854𝐸+01	−3.5962𝐸+01	−3.0634𝐸+01
T06	SaDE	−1.6865𝐸+01	—	−2.3470𝐸+01	—	−2.4051𝐸+01	—
	SaCDEhaS	−1.8954𝐸+01	−1.6577𝐸+01	−2.3229𝐸+01	−1.8566𝐸+01	−2.6803𝐸+01	−2.0694𝐸+00
T07	SaDE	6.8042𝐸−01	1.1232𝐸+00	5.0000𝐸−01	9.5787𝐸−01	5.0000𝐸−01^∗	8.4480𝐸−01
	SaCDEhaS	5.6924𝐸−01	1.2145𝐸+00	5.0000𝐸−01	8.7375𝐸−01	5.0000𝐸−01^∗	7.9041𝐸−01
T10	SaDE	−2.1774𝐸+01	−2.1167𝐸+01	−2.1780𝐸+01	−2.1250𝐸+01	−2.1780𝐸+01	−2.1299𝐸+01
	SaCDEhaS	−2.1725𝐸+01	−2.1122𝐸+01	−2.1834𝐸+01	−2.1345𝐸+01	−2.1835𝐸+01	2.6919𝐸−01
T12	SaDE	9.4639𝐸+00	1.4507𝐸+01	8.8193𝐸+00	1.3967𝐸+01	8.7939𝐸+00	1.3823𝐸+01
	SaCDEhaS	7.4100𝐸+00	1.4350𝐸+01	7.0985𝐸+00	1.3966𝐸+01	6.7105𝐸+00^∗	2.9544𝐸+00
T13	SaDE	1.0625𝐸+01	1.8921𝐸+01	1.0129𝐸+01	1.8378𝐸+01	1.0126𝐸+01	1.8248𝐸+01
	SaCDEhaS	9.3750𝐸+00	1.9608𝐸+01	8.6945𝐸+00	1.8808𝐸+01	8.6626𝐸+00	4.3153𝐸+00

“—” denotes that the value is larger than 1𝐸+16. ∗Marks that the current best value is obtained.