The strategy of improving convergence of genetic algorithm

Jiang Jing, Meng Lidong


Premature convergence is the main obstacle to the application of genetic algorithm.  The study on convergence of GA is always one of the most important theoretical issues. Via analyzing the convergence rate of GA, the average computational complexity can be implied and the optimization efficiency of GA can be judged. This paper proposed an approach to calculating the first expected hitting time and analyzed the bounds of the first hitting time of concrete GA using the proposed approach. And this paper proposed a strategy which included  transformation of fitness function, self-adaptive crossover and mutation probability and close relative breeding avoidance method in order to overcome premature convergence.



Full Text:

Total views : 67 times


  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

shopify stats IJEECS visitor statistics