A Memetic Differential Evolution Algorithm Based on Dynamic Preference for Constrained Optimization Problems

Table 3

Results of the approximate two-sample 𝑡-test between the other three algorithms and our MDEDP for six instances.

Algorithms	𝑡-test	g02	g05	g07	g09	g10	g13
SR-MDEDP	𝑡0	−𝟑.𝟎𝟗^b	𝟑.𝟕𝟑^a	𝟓.𝟔𝟒^a	𝟒.𝟏𝟗^a	𝟓.𝟐𝟕^a	𝟐.𝟒𝟎^a
	𝑓	45	30	30	30	30	30
ATMES-MDEDP	𝑡0	−𝟒.𝟒𝟐^b	𝟑.𝟓𝟎^a	𝟒.𝟗𝟖^a	𝟓.𝟐𝟔^a	𝟗.𝟏𝟖^a	2.04
	𝑓	36	30	30	30	30	30
CBBO-MDEDP	𝑡0	−𝟓.𝟎𝟏^b	𝟑𝟐.𝟏𝟐^a	𝟏𝟔.𝟒𝟑^a	—	𝟏𝟕.𝟏𝟐^a	NA
	𝑓	30	30	30	—	30	NA