Title :
How to select optimal control parameters for genetic algorithms
Author :
Yang, Qi-Wen ; Jiang, Jing-Ping ; Chen, Guo
Author_Institution :
Coll. of Electr. Eng., Zhejiang Univ., China
Abstract :
In order to enhance the optimization efficiency, it´s important for genetic algorithms (GAs) to select optimal control parameters. But the theory behind parameter setting for a GA gives little guidance for their selection. We have being selected the control parameters for GAs only by trials so far. In this paper, we discuss the function of genetic operators and present the conception of natality of schema (NS). We put forward an approach to estimating the optimal ranges of the control parameters for GAs by utilizing the NS. The approach is proven effectively by a genetic algorithm based on Boolean operators (GABO) which is proposed in this paper
Keywords :
Boolean algebra; genetic algorithms; Boolean operators; genetic algorithms; genetic operators; natality of schema; optimal control parameters; optimization efficiency; Educational institutions; Evolution (biology); Genetic algorithms; Genetic mutations; Heuristic algorithms; Machine learning algorithms; Optimal control; Optimization methods; Space technology; Testing;
Conference_Titel :
Industrial Electronics, 2000. ISIE 2000. Proceedings of the 2000 IEEE International Symposium on
Conference_Location :
Cholula, Puebla
Print_ISBN :
0-7803-6606-9
DOI :
10.1109/ISIE.2000.930482