DocumentCode
2244897
Title
An improved genetic algorithm and its performance analysis
Author
Pi, Luo ; Jianfu, Teng ; Jichang, Guo ; Qiang, LI
Author_Institution
Sch. of Electron. & Inf. Eng., Tianjin Univ., China
Volume
4
fYear
2001
fDate
2001
Firstpage
329
Abstract
In the paper, some general theorems-minimal resolution, weight value, and searching step of crossover and mutation of the chromosome searching step in a genetic algorithm based on binary coding, one-point, crossover, and bit mutation are proposed and proved. Based on these theorems, an improved genetic algorithm using variant chromosome length and probability of crossover and mutation is presented. Finally, testing with some critical functions shows that it can improve the convergence speed of the genetic algorithm significantly and it accords with theoretic deduction, and its comprehensive performance is better than that of the genetic algorithm which only reserves the best individual
Keywords
convergence; genetic algorithms; probability; binary coding; bit mutation; convergence speed; improved genetic algorithm; minimal resolution; mutation; one-point crossover; performance analysis; searching; variant chromosome length; weight value; Biological cells; Computational modeling; Convergence; Genetic algorithms; Genetic engineering; Genetic mutations; Parallel processing; Performance analysis; Robustness; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Info-tech and Info-net, 2001. Proceedings. ICII 2001 - Beijing. 2001 International Conferences on
Conference_Location
Beijing
Print_ISBN
0-7803-7010-4
Type
conf
DOI
10.1109/ICII.2001.983840
Filename
983840
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