English

Variations of Genetic Algorithms

Neural and Evolutionary Computing 2019-11-04 v1 Machine Learning

Abstract

The goal of this project is to develop the Genetic Algorithms (GA) for solving the Schaffer F6 function in fewer than 4000 function evaluations on a total of 30 runs. Four types of Genetic Algorithms (GA) are presented - Generational GA (GGA), Steady-State (mu+1)-GA (SSGA), Steady-Generational (mu,mu)-GA (SGGA), and (mu+mu)-GA.

Keywords

Cite

@article{arxiv.1911.00490,
  title  = {Variations of Genetic Algorithms},
  author = {Alison Jenkins and Vinika Gupta and Alexis Myrick and Mary Lenoir},
  journal= {arXiv preprint arXiv:1911.00490},
  year   = {2019}
}

Comments

genetic algorithm, elitism, generational, steady-state

R2 v1 2026-06-23T12:02:30.131Z