Self-adaptive, multipopulation differential evolution in dynamic environments

Abstract:

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. © 2013 Springer-Verlag Berlin Heidelberg.

Año de publicación:

2013

Keywords:

• Self-adaptation
• Differential Evolution
• Dynamic environments

Fuente:

scopus