Crossover and mutation operators of genetic algorithms
Genetic algorithms (GA) are stimulated by population genetics and evolution at the population level where crossover and mutation comes from random variables. The problems of slow and premature convergence to suboptimal solution remain an existing struggle that GA is facing. Due to lower diversity in...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
International Association of Computer Science and Information Technology
2017
|
| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/3688/1/AJ%202017%20%28515%29.pdf |