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

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Publicat a:International Journal of Swarm Intelligence Research vol. 16, no. 1 (2025), p. 1-39
Autor principal: Yuan, Qihang
Altres autors: Zhang, Yongde, Muzzammil, Hafiz Muhammad
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IGI Global
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MARC

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022 |a 1947-9263 
022 |a 1947-9271 
024 7 |a 10.4018/IJSIR.378562  |2 doi 
035 |a 3219011944 
045 2 |b d20250101  |b d20251231 
100 1 |a Yuan, Qihang  |u Harbin University of Science and Technology, China 
245 1 |a A Modified Artificial Rabbits Optimization for Solving Numerical Functions and Engineering Problems 
260 |b IGI Global  |c 2025 
513 |a Journal Article 
520 3 |a 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. 
653 |a Accuracy 
653 |a Swarm intelligence 
653 |a Engineering 
653 |a Physics 
653 |a Convergence 
653 |a Evolution 
653 |a Artificial intelligence 
653 |a Exploitation 
653 |a Optimization algorithms 
653 |a Optimization techniques 
653 |a Optimization 
700 1 |a Zhang, Yongde  |u Harbin University of Science and Technology, China 
700 1 |a Muzzammil, Hafiz Muhammad  |u Harbin University of Science and Technology, China 
773 0 |t International Journal of Swarm Intelligence Research  |g vol. 16, no. 1 (2025), p. 1-39 
786 0 |d ProQuest  |t Engineering Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3219011944/abstract/embedded/75I98GEZK8WCJMPQ?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3219011944/fulltextPDF/embedded/75I98GEZK8WCJMPQ?source=fedsrch