A New Kind of Fuzzy Genetic Algorithm

LI Qing; ZHENG Deling; TANG Yong; CHEN Zhanying

doi:10.13374/j.issn1001-053x.2001.01.050

Volume 23 Issue 1

Aug. 2021

Turn off MathJax

Article Contents

Article Navigation > Chinese Journal of Engineering > 2001 > 23(1): 85-89

LI Qing, ZHENG Deling, TANG Yong, CHEN Zhanying. A New Kind of Fuzzy Genetic Algorithm[J]. Chinese Journal of Engineering, 2001, 23(1): 85-89. doi: 10.13374/j.issn1001-053x.2001.01.050

Citation:

LI Qing, ZHENG Deling, TANG Yong, CHEN Zhanying. A New Kind of Fuzzy Genetic Algorithm[J]. Chinese Journal of Engineering, 2001, 23(1): 85-89. doi: 10.13374/j.issn1001-053x.2001.01.050

LI Qing, ZHENG Deling, TANG Yong, CHEN Zhanying. A New Kind of Fuzzy Genetic Algorithm[J]. Chinese Journal of Engineering, 2001, 23(1): 85-89. doi: 10.13374/j.issn1001-053x.2001.01.050

Citation:

LI Qing, ZHENG Deling, TANG Yong, CHEN Zhanying. A New Kind of Fuzzy Genetic Algorithm[J]. Chinese Journal of Engineering, 2001, 23(1): 85-89. doi: 10.13374/j.issn1001-053x.2001.01.050

PDF( 476 KB)

A New Kind of Fuzzy Genetic Algorithm

doi: 10.13374/j.issn1001-053x.2001.01.050

1. Information Engineering School, UST Beijing, Beijing 100083, China;
2. Automation Research Institute of the Ministry of Metallurgical Industry Beijing 100071, China

Received Date: 2000-06-18

Abstract

Abstract

The fuzzy control method is mixed into the genetic algorithm to adjust the probabilities of crossover and mutation. A new improved genetic algorithm named the fuzzy genetic algorithm (FGA) is proposed. Simulation results show that FGA is very efficiency for the quality of the solution is improved and the convergent speed of the solution is accelerated.
- genetic algorithm,
- fuzzy control,
- crossover probability,
- mutation probability