Title :
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
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;
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
DOI :
10.1109/ISdea.2012.490
