Enhanced secretary bird optimization algorithm with multi-strategy fusion and Cauchy-Gaussian crossover

To address the issues of low convergence accuracy and susceptibility to local optima in the Secretary Bird Optimization Algorithm (SBOA), this paper proposes an improved algorithm (UTFSBOA) that integrates multi-strategy collaboration and Cauchy-Gaussian crossover. The algorithm introduces three innovative mechanisms. First, it incorporates an adaptive nonlinear factor-based directional search mechanism to enhance global exploration. Second, it uses an exponentially decaying energy escape factor inspired by Harris Hawk Optimization (HHO) to balance exploration and exploitation. Third, it includes a Cauchy-Gaussian crossover strategy to enrich solution diversity and prevent premature convergence. Experimental evaluations on the CEC2005 benchmark functions demonstrate that UTFSBOA achieves 81.18% and 88.22% improvements in average convergence accuracy over SBOA in 30-dimensional and 100-dimensional scenarios, respectively. Among 12 complex functions in the CEC2022 test set, the proposed algorithm obtains optimal solutions for 7 functions. Statistical validation via Wilcoxon rank-sum and Friedman tests confirms its robustness. Validation through four real-world engineering problems further confirms its superiority in constrained and discrete optimization scenarios, with objective function improvements reaching up to 91.3%. The results prove that multi-strategy synergy significantly enhances algorithmic robustness in high-dimensional complex spaces, establishing UTFSBOA as an effective solution for constrained and discrete optimization challenges.