Adaptive Self-Scaling Brain-Storm Optimization via a Chaotic Search Mechanism

Brain-storm optimization (BSO), which is a population-based algorithm, exhibits poor search performance, premature convergence, and high probability of falling into local optima. To address these problems, we developed the adaptive mechanism-based BSO (ABSO) algorithm based on chaotic in this study. The adjustment space using method an self-scaling mechanism balances global development performance ABSO effectively preventing from optima improving its convergence accuracy. verify stability effectiveness proposed was tested 29 benchmark test functions, mean standard deviation were compared with those five other algorithms. results showed that outperforms algorithms terms In addition, further verified through nonparametric statistical test.