Differential evolution with automatic parameter configuration for solving the CEC2013 competition on Real-Parameter Optimization

Author

Elsayed, Saber M. ; Sarker, Ruhul A. ; Ray, Tapabrata

Author_Institution

Sch. of Eng. & Inf. Technol., Univ. of New South Wales, Canberra, ACT, Australia

fYear

2013

fDate

20-23 June 2013

Firstpage

1932

Lastpage

1937

Abstract

The performance of Differential Evolution (DE) algorithms is known to be highly dependent on its search operators and control parameters. The selection of the parameter values is a tedious task. In this paper, a DE algorithm is proposed that configures the values of two parameters (amplification factor and crossover rate) automatically during its course of evolution. For this purpose, we considered a set of values as input for each of the parameters. The algorithm has been applied to solve a set of test problems introduced in IEEE CEC´2013 competition. The results of the test problems are compared with the known best solutions and the approach can be applied to other population based algorithms.

Keywords

evolutionary computation; optimisation; DE algorithm; IEEE CEC2013 Competition; amplification factor; automatic parameter configuration; control parameters; crossover rate; differential evolution; population based algorithms; real-parameter optimization; search operators; Algorithm design and analysis; Equations; Gaussian distribution; Optimization; Sociology; Statistics; Vectors; differential evolution; parameter configuration;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation (CEC), 2013 IEEE Congress on

Conference_Location

Cancun

Print_ISBN

978-1-4799-0453-2

Electronic_ISBN

978-1-4799-0452-5

Type

conf

DOI

10.1109/CEC.2013.6557795

Filename

6557795