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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Veröffentlicht in:The Journal of supercomputing Jg. 79; H. 7; S. 7305 - 7336
Hauptverfasser: Xue, Jiankai, Shen, Bo
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Springer US 01.05.2023
Springer Nature B.V
Schlagworte:
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
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Zusammenfassung: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.
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ISSN:0920-8542
1573-0484
DOI:10.1007/s11227-022-04959-6