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

Qihang Yuan, Yongde Zhang and Hafiz Muhammad Muzzammil
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Qihang Yuan: Harbin University of Science and Technology, China
Yongde Zhang: Harbin University of Science and Technology, China
Hafiz Muhammad Muzzammil: Harbin University of Science and Technology, China

International Journal of Swarm Intelligence Research (IJSIR), 2025, vol. 16, issue 1, 1-38

Abstract: 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.

Date: 2025
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