A genetic algorithm for solving the CEC´2013 competition problems on real-parameter optimization

Author

Elsayed, Saber M. ; Sarker, Ruhul A. ; Essam, Daryl L.

Author_Institution

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

fYear

2013

fDate

20-23 June 2013

Firstpage

356

Lastpage

360

Abstract

Many genetic algorithms variants have been introduced for solving different classes of optimization problems. The success of any GA depends on the design of its search operators, as well as its parameters. In this paper, we propose a new three-parent crossover. In addition, we design a diversity operator which works with an archive of selected individuals. The algorithm has been applied to solve all the CEC´2013 competition problems on real-parameter optimization. The solutions obtained are either optimal or very close to the known best solutions.

Keywords

genetic algorithms; mathematical operators; search problems; CEC´2013 competition problems; diversity operator; genetic algorithm variants; optimization problems; real-parameter optimization; search operators; three-parent crossover; Algorithm design and analysis; Evolutionary computation; Genetic algorithms; Optimization; Sociology; Statistics; Vectors; Numerical optimization; genetic algorithms; multi-parent crossover;

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.2013.6557591

Filename

6557591