An Improved Genetic Algorithm and its Application in Routing Optimization

Traditional routing algorithms can't adapt to the complex and changeable network environment, and the basic genetic algorithm can't be applied to solving routing optimization problems directly because of the lack of coding methods. An improved basic genetic algorithm was purposed to find the optimal or near-optimal routing. The network model and mathematical expression of routing optimization problem was defined, and the routing problem was transformed into a problem of finding the optimal solution. In order to meet the specific needs of network routing optimization, some key improvements of GA have been made, including the design of coding scheme, the generation of initial population, the construction of fitness function and the improvement of crossover operator and mutation operator. The simulation results of two typical network environments show that the improved GA has excellent performance in routing optimization. Compared with Dijkstra algorithm and Floyd algorithm, the improved GA in this paper not only has excellent robustness and adaptability in solving routing optimization problems, but also can effectively cope with the dynamic changes of network environment, providing an efficient and reliable routing solution for dynamic network environment.

@article{Wang2024,
  title     = {An Improved Genetic Algorithm and its Application in Routing Optimization},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {15},
  number    = {7},
  year      = {2024},
  publisher = {The Science and Information Organization},
  author    = {Jianwei Wang and Wenjuan Sun},
  doi       = {10.14569/IJACSA.2024.01507117},
  url       = {https://doi.org/10.14569/IJACSA.2024.01507117}
}