.png){kind=icon}
Return
Self-adaptive, multipopulation differential evolution in dynamic environments
.png){kind=icon}
PRE
AI
DOI：10.1007/s00500-013-1022-x.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
The present work proposes a simple but effective self-adaptive strategy to control the behaviour of a differential evolution (DE) based multipopulation algorithm for dynamic environments. Specifically, the proposed scheme is aimed to control the creation of random individuals by the self-adaptation of the involved parameter. An interaction scheme between random and conventional DE individuals is also proposed and analyzed. The conducted computational experiments show that self-adaptation is profitable, leading to an algorithm that is as competitive as other efficient methods and able to beat the winner of the CEC 2009 competition on dynamic environments.
Keywords:
Differential evolution
Self-adaptation
Dynamic environments
Journal
IF:
2.5
Papers:
1.0W
Citations:
2.1W
Organization
Cited Papers
ShareSaveScalability of generalized adaptive differential evolution for large-scale continuous optimization.png)
SOFT COMPUTING
SOFT COMPUTINGIF2.5
PREAI
ShareSave
ShareSaveShareSave
View more