A Genetic Algorithm Based on a New Real Coding Approach

Author

Zhang, Guoshan ; Liu, Wanliang

Author_Institution

Sch. of Electr. Eng. & Autom., Tianjin Univ., Tianjin, China

fYear

2012

Firstpage

88

Lastpage

92

Abstract

Genetic algorithm is a kind of common method to solve nonlinear programming problems. To improve the computational efficiency of the algorithm, a genetic algorithm based on a new real code (NRCGA) was proposed, which could solve a class of nonlinear programming problems. The new real coded strategy can be used to repair all of the infeasible chromosomes by simply sorting and keeping search within the feasible region. NRCGA is more accurate than the existing methods on equality constraint handling. Many examples show that the new algorithm has high search efficiency and strong robustness.

Keywords

constraint handling; genetic algorithms; nonlinear programming; search problems; algorithm computational efficiency; equality constraint handling; genetic algorithm; infeasible chromosomes; nonlinear programming problems; real coding approach; search efficiency; Algorithm design and analysis; Biological cells; Decoding; Encoding; Evolutionary computation; Genetic algorithms; Optimization; constraint-handling; genetic algorithm; nonlinear programming; penalty functions; real-coding;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent System Design and Engineering Application (ISDEA), 2012 Second International Conference on

Conference_Location

Sanya, Hainan

Print_ISBN

978-1-4577-2120-5

Type

conf

DOI

10.1109/ISdea.2012.490

Filename

6173154