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Related Experiment Video

Updated: Sep 17, 2025

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

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

Xinle Wang¹, Peijun Wei¹, Yancang Li²

¹School of Civil Engineering, Hebei University of Engineering, Handan, 056038, Hebei, China.

Scientific Reports

|July 2, 2025

Summary

This study introduces an improved Secretary Bird Optimization Algorithm (UTFSBOA) that enhances convergence accuracy and avoids local optima. The novel algorithm demonstrates superior performance in complex, high-dimensional optimization problems.

Keywords:

Adaptive factor Cauchy–Gaussian crossover Directional search strategy Energy escape factor Secretary bird optimization algorithm

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Last Updated: Sep 17, 2025

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Area of Science:

Computational Intelligence
Metaheuristic Optimization
Algorithm Design

Background:

Secretary Bird Optimization Algorithm (SBOA) suffers from low convergence accuracy and local optima.
Existing optimization algorithms often struggle with high-dimensional and complex problem spaces.

Purpose of the Study:

To propose an improved algorithm, UTFSBOA, addressing SBOA's limitations.
To enhance global exploration, balance exploitation, and enrich solution diversity in optimization.

Main Methods:

Integration of multi-strategy collaboration and Cauchy-Gaussian crossover into SBOA.
Introduction of an adaptive nonlinear factor-based directional search.
Incorporation of an exponentially decaying energy escape factor inspired by Harris Hawk Optimization (HHO).

Main Results:

UTFSBOA achieved 81.18% and 88.22% higher convergence accuracy than SBOA in 30D and 100D scenarios.
Obtained optimal solutions for 7 out of 12 complex functions in the CEC2022 test set.
Demonstrated significant improvements (up to 91.3%) on real-world engineering problems.

Conclusions:

Multi-strategy synergy significantly enhances algorithmic robustness in high-dimensional complex spaces.
UTFSBOA is an effective solution for constrained and discrete optimization challenges.
The proposed enhancements overcome the limitations of the original SBOA.