Research of Multi Population Differential Evolution Algorithm

The standard differential evolution is easy to fall into premature convergence; so for solving the problem, the paper presented a Multi Population Differential Evolution Algorithm (MPDE) which was based on simulating the developing history of human races. The population was divided into several subp...

Full description

Saved in:
Bibliographic Details
Published in2009 Fifth International Conference on Natural Computation Vol. 1; pp. 261 - 264
Main Authors Chen Xiqu, Wang Zhankui, Du Jiaxi, Pang Minghua
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2009
Subjects
Communication system control
Convergence
Differential evolution algorithm
History
Humans
Multi population
Optimization
Optimization methods
Paper technology
Probability distribution
Random number generation
Stability
Standards development
Online AccessGet full text

Cover

More Information
Summary:The standard differential evolution is easy to fall into premature convergence; so for solving the problem, the paper presented a Multi Population Differential Evolution Algorithm (MPDE) which was based on simulating the developing history of human races. The population was divided into several subpopulations in MPDE, which can enhance the searching capacity of the algorithm. Finally, three experiments were done on benchmark functions, the results show that MPDE has a good global searching capacity than DE and could avoid premature convergence.
ISBN:0769537367
9780769537368
ISSN:2157-9555
DOI:10.1109/ICNC.2009.412