Title :
Enhanced genetic algorithm in electric network planning
Author :
Danhong, Zhong ; Jie, Wu ; Dejian, Kong
Author_Institution :
South China Univ. of Technol., Guangzhou, China
Abstract :
This paper studies effects of the new generation forming method in genetic algorithm. After discussing the characteristics of electric network planning, an enhanced genetic algorithm approach is described, which introduces an adaptive generation gap. Example is given to prove that it can improve the algorithm both in speed and accuracy
Keywords :
adaptive control; genetic algorithms; power transmission planning; adaptive control; electric network planning; generation gap; genetic algorithm; Character generation; Genetic algorithms; Intelligent networks; Power generation; Probes; Technology planning;
Conference_Titel :
Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on
Conference_Location :
Hefei
Print_ISBN :
0-7803-5995-X
DOI :
10.1109/WCICA.2000.859914
