Review of Parameter Tuning Methods for Nature-Inspired Algorithms
Benchmarks and Hybrid Algorithms in Optimization and Applications, 2023•Springer
Almost all optimization algorithms have algorithm-dependent parameters, and the setting of
such parameter values can largely influence the behavior 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 …
such parameter values can largely influence the behavior 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 …
Abstract
Almost all optimization algorithms have algorithm-dependent parameters, and the setting of such parameter values can largely influence the behavior 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.
Springer
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