Review of Parameter Tuning Methods for Nature-Inspired Algorithms
This is an incremental review that addresses the problem of parameter tuning for researchers and practitioners using nature-inspired algorithms.
This paper reviews methods for tuning parameters in nature-inspired optimization algorithms, highlighting that proper tuning is crucial for performance and robustness across different problems, and it discusses open issues and future research directions.
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.