Analysis of Parameter Settings for the Bat Algorithm Using Variance Evolution
Parameter settings in evolutionary algorithms and metaheuristics are important because such parameter values can influence the performance of algorithms under evaluation. For a given algorithm, there are many different numerical experiments to show that the algorithm can work well in practice; however, in most cases there is no theoretical analysis of parameter settings. In this work, we show that theoretical analysis using the theory of dynamical systems and evolution of population variance can give some good results in terms of parameter ranges for the bat algorithm. We also show that results from numerical experiments are consistent with theoretical bounds. Such analyses can provide go...
| Authors | Xin-She Yang, Mehmet Karamanoglu |
|---|---|
| Primary category | cs.NE |
| Published | 26 June 2026 |
| Last updated at source | 26 June 2026 |
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