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A Modified Artificial Rabbits Optimization for Solving Numerical Functions and Engineering Problems

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Publicado en:International Journal of Swarm Intelligence Research vol. 16, no. 1 (2025), p. 1-39
Autor principal: Yuan, Qihang
Otros Autores: Zhang, Yongde, Muzzammil, Hafiz Muhammad
Publicado:
IGI Global
Materias:
Accuracy
Swarm intelligence
Engineering
Physics
Convergence
Evolution
Artificial intelligence
Exploitation
Optimization algorithms
Optimization techniques
Optimization
Acceso en línea:Citation/Abstract
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Resumen:The recently proposed swarm intelligence Artificial Rabbits Optimization (ARO) performs well, but there are still some drawbacks, including low population diversity, unbalanced exploration and exploitation capabilities, and low convergence accuracy. To address the above issues, this article proposes a variant of ARO named MARO, which adopts three strategies to overcome the limitations of ARO and improve its performance. This paper uses 23 classic test functions and CEC2017 test functions for testing. The experimental results show that MARO has higher convergence speed, accuracy, and stability than the comparison algorithms. In addition, the enormous potential of MARO in practical applications is further verified through five real-world engineering application problems.
ISSN:1947-9263
1947-9271
DOI:10.4018/IJSIR.378562
Fuente:Engineering Database