A Comparison between Chemical Reaction Optimization and Genetic Algorithms for Max Flow Problem

This paper presents a comparison between the performance of Chemical Reaction Optimization algorithm and Genetic algorithm in solving maximum flow problem with the performance of Ford-Fulkerson algorithm in that. The algorithms have been implemented sequentially using JAVA programming language, and executed to find maximum flow problem using different network size. Ford-Fulkerson algorithm which is based on the idea of finding augmenting path is the most popular algorithm used to find maximum flow value but its time complexity is high. The main aim of this study is to determine which algorithm will give results closer to the Ford-Fulkerson results in less time and with the same degree of accuracy. The results showed that both algorithms can solve Max Flow problem with accuracy results close to Ford Fulkerson results, with a better performance achieved when using the genetic algorithm in term of time and accuracy.

@article{Khanafseh2017,
  title     = {A Comparison between Chemical Reaction Optimization and Genetic Algorithms for Max Flow Problem},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {8},
  number    = {8},
  year      = {2017},
  publisher = {The Science and Information Organization},
  author    = {Mohammad Y. Khanafseh and Ola M. Surakhi and Ahmad Sharieh and Azzam Sleit},
  doi       = {10.14569/IJACSA.2017.080802},
  url       = {https://doi.org/10.14569/IJACSA.2017.080802}
}