Enhanced mutation strategy for differential evolution

Author

Kumar, Pravesh ; Pant, Millie

Author_Institution

DPT, Indian Inst. of Technol., Roorkee, India

fYear

2012

fDate

10-15 June 2012

Firstpage

1

Lastpage

6

Abstract

It is well known that mutation plays a very important role in the successful performance of Differential Evolution (DE) algorithm. The proposed scheme named Modified Random Localization (MRL) is based on strategically selecting the individuals from the entire search space rather than choosing them randomly as in basic DE. The corresponding DE variant named MRL-DE is analyzed on a set of 8 traditional benchmark functions and 6 nontraditional shifted functions. Numerical and statistical results indicate the competence of the proposed MRL-DE for solving unconstrained global optimization problems.

Keywords

evolutionary computation; optimisation; search problems; MRL-DE; differential evolution algorithm; enhanced mutation strategy; modified random localization; nontraditional shifted functions; search space; statistical results; unconstrained global optimization problems; Algorithm design and analysis; Benchmark testing; Convergence; Optimization; Standards; Statistical analysis; Vectors; differential evolution; mutation; perturbed vector; randomized localization;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation (CEC), 2012 IEEE Congress on

Conference_Location

Brisbane, QLD

Print_ISBN

978-1-4673-1510-4

Electronic_ISBN

978-1-4673-1508-1

Type

conf

DOI

10.1109/CEC.2012.6252914

Filename

6252914