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

DOI:

https://doi.org/10.14419/jacst.v8i2.29401

Keywords:

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