Dung beetle optimizer: a new meta-heuristic algorithm for global optimization

In this paper, a novel population-based technique called dung beetle optimizer (DBO) algorithm is presented, which is inspired by the ball-rolling, dancing, foraging, stealing, and reproduction behaviors of dung beetles. The newly proposed DBO algorithm takes into account both the global exploration...

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Bibliographic Details
Published in:	The Journal of supercomputing Vol. 79; no. 7; pp. 7305 - 7336
Main Authors:	Xue, Jiankai, Shen, Bo
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.05.2023 Springer Nature B.V
Subjects:	Accuracy Algorithms Beetles Behavior Compilers Computer Science Convergence Design Design engineering Dung Functions (mathematics) Global optimization Heuristic methods Interpreters Mathematical programming Optimization algorithms Optimization techniques Processor Architectures Programming Languages Rank tests Convergence rate Engineering applications Swarm intelligence Dung beetle optimizer (DBO) Particle swarm optimization (PSO)
ISSN:	0920-8542, 1573-0484
Online Access:	Get full text
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Abstract	In this paper, a novel population-based technique called dung beetle optimizer (DBO) algorithm is presented, which is inspired by the ball-rolling, dancing, foraging, stealing, and reproduction behaviors of dung beetles. The newly proposed DBO algorithm takes into account both the global exploration and the local exploitation, thereby having the characteristics of the fast convergence rate and the satisfactory solution accuracy. A series of well-known mathematical test functions (including both 23 benchmark functions and 29 CEC-BC-2017 test functions) are employed to evaluate the search capability of the DBO algorithm. From the simulation results, it is observed that the DBO algorithm presents substantially competitive performance with the state-of-the-art optimization approaches in terms of the convergence rate, solution accuracy, and stability. In addition, the Wilcoxon signed-rank test and the Friedman test are used to evaluate the experimental results of the algorithms, which proves the superiority of the DBO algorithm against other currently popular optimization techniques. In order to further illustrate the practical application potential, the DBO algorithm is successfully applied in three engineering design problems. The experimental results demonstrate that the proposed DBO algorithm can effectively deal with real-world application problems.
AbstractList	In this paper, a novel population-based technique called dung beetle optimizer (DBO) algorithm is presented, which is inspired by the ball-rolling, dancing, foraging, stealing, and reproduction behaviors of dung beetles. The newly proposed DBO algorithm takes into account both the global exploration and the local exploitation, thereby having the characteristics of the fast convergence rate and the satisfactory solution accuracy. A series of well-known mathematical test functions (including both 23 benchmark functions and 29 CEC-BC-2017 test functions) are employed to evaluate the search capability of the DBO algorithm. From the simulation results, it is observed that the DBO algorithm presents substantially competitive performance with the state-of-the-art optimization approaches in terms of the convergence rate, solution accuracy, and stability. In addition, the Wilcoxon signed-rank test and the Friedman test are used to evaluate the experimental results of the algorithms, which proves the superiority of the DBO algorithm against other currently popular optimization techniques. In order to further illustrate the practical application potential, the DBO algorithm is successfully applied in three engineering design problems. The experimental results demonstrate that the proposed DBO algorithm can effectively deal with real-world application problems.
Author	Xue, Jiankai Shen, Bo
Author_xml	– sequence: 1 givenname: Jiankai surname: Xue fullname: Xue, Jiankai organization: College of Information Science and Technology, Donghua University, Engineering Research Center of Digitalized Textile and Fashion Technology, Ministry of Education – sequence: 2 givenname: Bo surname: Shen fullname: Shen, Bo email: bo.shen@dhu.edu.cn organization: College of Information Science and Technology, Donghua University, Engineering Research Center of Digitalized Textile and Fashion Technology, Ministry of Education
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Snippet	In this paper, a novel population-based technique called dung beetle optimizer (DBO) algorithm is presented, which is inspired by the ball-rolling, dancing,...
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SubjectTerms	Accuracy Algorithms Beetles Behavior Compilers Computer Science Convergence Design Design engineering Dung Functions (mathematics) Global optimization Heuristic methods Interpreters Mathematical programming Optimization algorithms Optimization techniques Processor Architectures Programming Languages Rank tests
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Title	Dung beetle optimizer: a new meta-heuristic algorithm for global optimization
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