Review of Parameter Tuning Methods for Nature-Inspired Algorithms

TL;DR

This paper reviews various parameter tuning methods for nature-inspired algorithms, emphasizing their importance for optimizing performance and robustness, and discusses recent developments, open problems, and future research directions.

Contribution

It provides a comprehensive overview of current parameter tuning techniques and highlights recent advancements and challenges in the field.

Findings

Summarizes main parameter tuning methods

Identifies key issues in recent developments

Suggests future research directions

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.