Review of Parameter Tuning Methods for Nature-Inspired Algorithms
Artificial Intelligence
2023-08-31 v1 Neural and Evolutionary Computing
Optimization and Control
Abstract
Almost all optimization algorithms have algorithm-dependent parameters, and the setting of such parameter values can largely influence the behaviour of the algorithm under consideration. Thus, proper parameter tuning should be carried out to ensure the algorithm used for optimization may perform well and can be sufficiently robust for solving different types of optimization problems. This chapter reviews some of the main methods for parameter tuning and then highlights the important issues concerning the latest development in parameter tuning. A few open problems are also discussed with some recommendations for future research.
Cite
@article{arxiv.2308.15965,
title = {Review of Parameter Tuning Methods for Nature-Inspired Algorithms},
author = {Geethu Joy and Christian Huyck and Xin-She Yang},
journal= {arXiv preprint arXiv:2308.15965},
year = {2023}
}