Dhole Optimization Algorithm

Versión 1.3 (5,77 KB) por bnyad omar
The Dhole Optimization Algorithm (DOA) is a recently proposed metaheuristic algorithm designed to solve various optimization problems.
191 Descargas
Actualizado 4 ago 2025

Ver licencia

Dhole Optimization Algorithm: a New Metaheuristic Algorithm for Solving Optimization Problems
This paper presents the Dhole Optimization Algorithm (DOA), an innovative method inspired from the social and hunting activities of dholes, especially their vocal communication and coordination techniques. DOA simulates distinctive behaviors, including vocalization-driven adaptive decision-making and dynamic pack formation, which improve the balance between exploration and exploitation during the optimization process. The efficacy of DOA is assessed using 23 classical benchmark functions, in addition to the CEC-2019 and CEC-2022 benchmark sets, together with a range of real-world optimization problems. The findings indicate that DOA routinely attains competitive performance relative to established metaheuristic algorithms, frequently surpassing them in convergence time and robustness, especially for complex, high-dimensional problems. This work's primary contribution involves the development of a new nature-inspired optimization algorithm that incorporates adaptive methods inspired by dhole pack dynamics, accompanied by a comprehensive evaluation that underscores the strengths of DOA. The suggested DOA demonstrates a robust capacity to preserve variety, avoid local optima, and adjust to changing problem environments, rendering it a promising method for addressing complex optimization challenges and enhancing nature-inspired optimization methods.
If you find this work useful for your research, please cite it https://doi.org/10.1007/s10586-024-05005-1

Citar como

Mohammed, Bnyad O., et al. “Dhole Optimization Algorithm: a New Metaheuristic Algorithm for Solving Optimization Problems.” Cluster Computing, vol. 28, no. 7, July 2025, https://doi.org/10.1007/s10586-024-05005-1.

Ver más estilos
Compatibilidad con la versión de MATLAB
Se creó con R2025a
Compatible con cualquier versión
Compatibilidad con las plataformas
Windows macOS Linux

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!
Versión Publicado Notas de la versión
1.3

summary

1.2

image

1.1

Cite

1.0.0