An Improvement of Genetic Algorithm based on Dynamic Operators Rates Controlled by the Population Performance

Beatriz Azevedo, Beatriz Azevedo, Ana Pereira, Ana Pereira, Glaucia Bressan

2020

Abstract

This work presents a hybrid approach of genetic algorithm with dynamic operators rates that adapt to the phases of the evolutionary process. The operator’s rates are controlled by the amplitude variation and standard deviation of the objective function. Besides, a new stopping criterion is presented to be used in conjunction with the proposed algorithm. The developed approach is tested with six optimization benchmark functions from the literature. The results are compared to the genetic algorithm with constant rates in terms of the number of function evaluations, the number of iterations, execution time and optimum solution analysis.

Paper Citation

in Harvard Style

Azevedo B., Pereira A. and Bressan G. (2020). An Improvement of Genetic Algorithm based on Dynamic Operators Rates Controlled by the Population Performance. In Proceedings of the 9th International Conference on Operations Research and Enterprise Systems - Volume 1: ND2A, ISBN 978-989-758-396-4, pages 388-394. DOI: 10.5220/0009385403880394

in Bibtex Style

@conference{nd2a20,
author={Beatriz Azevedo and Ana Pereira and Glaucia Bressan},
title={An Improvement of Genetic Algorithm based on Dynamic Operators Rates Controlled by the Population Performance},
booktitle={Proceedings of the 9th International Conference on Operations Research and Enterprise Systems - Volume 1: ND2A,},
year={2020},
pages={388-394},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009385403880394},
isbn={978-989-758-396-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 9th International Conference on Operations Research and Enterprise Systems - Volume 1: ND2A,
TI - An Improvement of Genetic Algorithm based on Dynamic Operators Rates Controlled by the Population Performance
SN - 978-989-758-396-4
AU - Azevedo B.
AU - Pereira A.
AU - Bressan G.
PY - 2020
SP - 388
EP - 394
DO - 10.5220/0009385403880394