A comparative study of particle swarm optimization and genetic algorithm

  • Authors

    • Saman M. Almufti computer science
    • Amar Yahya Zebari Statistic
    • Herman Khalid Omer computer science

    Received date: May 29, 2019

    Accepted date: July 6, 2019

    Published date: October 19, 2019

    https://doi.org/10.14419/jacst.v8i2.29401
  • Particle Swarm Optimization (PSO), Genetic Algorithms (GAS), Swarm Intelligence, PSO and GA Comparison.

  • Abstract

    This paper provides an introduction and a comparison of two widely used evolutionary computation algorithms: Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) based on the previous studies and researches. It describes Genetic Algorithm basic functionalities including various steps such as selection, crossover, and mutation.

     

     

  • References

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  • How to Cite

    M. Almufti, S., Yahya Zebari, A., & Khalid Omer, H. (2019). A comparative study of particle swarm optimization and genetic algorithm. Journal of Advanced Computer Science & Technology, 8(2), 40-45. https://doi.org/10.14419/jacst.v8i2.29401

    Received date: May 29, 2019

    Accepted date: July 6, 2019

    Published date: October 19, 2019