Parameter Sensitivity Patterns in the Plant Propagation Algorithm

Marleen de Jonge, Daan van den Berg

2020

Abstract

The parameter sensitivity of the plant propagation algorithm’s performance, defined as the maximum impact on attained objective values, is studied on function optimization. The number of offspring and population size are varied across a large range of values and tested on multidimensional benchmark test functions. As the dimensionality of a function increases, the parametric sensitivity shows one of three distinct different patterns: sublinear increase, superlinear increase or an up-down phase transition. We conjecture that the difference in algorithmic behaviour might be due to the intrinsic mathematical properties of the functions themselves.

Paper Citation

in Harvard Style

de Jonge M. and van den Berg D. (2020). Parameter Sensitivity Patterns in the Plant Propagation Algorithm. In Proceedings of the 12th International Joint Conference on Computational Intelligence (IJCCI 2020) - Volume 1: ECTA; ISBN 978-989-758-475-6, SciTePress, pages 92-99. DOI: 10.5220/0010134300920099

in Bibtex Style

@conference{ecta20,
author={Marleen de Jonge and Daan van den Berg},
title={Parameter Sensitivity Patterns in the Plant Propagation Algorithm},
booktitle={Proceedings of the 12th International Joint Conference on Computational Intelligence (IJCCI 2020) - Volume 1: ECTA},
year={2020},
pages={92-99},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010134300920099},
isbn={978-989-758-475-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Computational Intelligence (IJCCI 2020) - Volume 1: ECTA
TI - Parameter Sensitivity Patterns in the Plant Propagation Algorithm
SN - 978-989-758-475-6
AU - de Jonge M.
AU - van den Berg D.
PY - 2020
SP - 92
EP - 99
DO - 10.5220/0010134300920099
PB - SciTePress