Research on optimization efficiency of Genetic Algorithms

Author(s):  
Sheng Liu ◽  
Gao-yun Li ◽  
Jia Song ◽  
Tian-ying Sun
2012 ◽  
Vol 479-481 ◽  
pp. 1745-1749
Author(s):  
Xing Li ◽  
Ya Zhou Chen

As designing the loader working device related to multi-variables, multi-objective and it is a non-linear constrained complex optimization problem essentially so using traditional optimization method to design the loader working device is low efficiency. A new method is proposed which combines the sensitivity analysis with the genetic algorithms to reduce the design variables and to improve the optimization efficiency. The optimization mathematical model is established. The key design variables which have greater impact on the loader digging force can be obtained by the sensitivity analysis and then input into genetic algorithms to conduct an optimization. By using this method the result showed that the loader digging force can be increased by 5.9 percent on the premise of meeting the overall performance requirements of the loader.


1996 ◽  
Vol 47 (4) ◽  
pp. 550-561 ◽  
Author(s):  
Kathryn A Dowsland
Keyword(s):  

2018 ◽  
Vol 1 (1) ◽  
pp. 2-19
Author(s):  
Mahmood Sh. Majeed ◽  
Raid W. Daoud

A new method proposed in this paper to compute the fitness in Genetic Algorithms (GAs). In this new method the number of regions, which assigned for the population, divides the time. The fitness computation here differ from the previous methods, by compute it for each portion of the population as first pass, then the second pass begin to compute the fitness for population that lye in the portion which have bigger fitness value. The crossover and mutation and other GAs operator will do its work only for biggest fitness portion of the population. In this method, we can get a suitable and accurate group of proper solution for indexed profile of the photonic crystal fiber (PCF).


2011 ◽  
Vol 3 (6) ◽  
pp. 87-90
Author(s):  
O. H. Abdelwahed O. H. Abdelwahed ◽  
◽  
M. El-Sayed Wahed ◽  
O. Mohamed Eldaken

2011 ◽  
Vol 2 (3) ◽  
pp. 56-58
Author(s):  
Roshni .V Patel ◽  
◽  
Jignesh. S Patel

Sign in / Sign up

Export Citation Format

Share Document