Dingo Optimization Algorithm (DOA)
Version 1.0.2 (9,37 ko) par
Hernan Peraza
A novel bio-inspired algorithm, namely Dingo Optimization Algorithm, is proposed for solving optimization problems.
A novel bio-inspired algorithm, namely Dingo Optimization Algorithm (DOA), is proposed for solving optimization problems. The DOA mimics the social behavior of the Australian dingo dog. The algorithm is inspired by the hunting strategies of dingoes which are: attacking by persecution, grouping tactics, and scavenging behavior. In order to increment the overall efficiency and performance of this method, three search strategies associated with four rules were formulated in the DOA. These strategies and rules provide a fine balance between the intensification (exploitation) and diversification (exploration) over the search space. The proposed method is verified using several benchmark problems commonly used in the optimization field, classical design engineering problems, and optimal tuning of a Proportional-Integral- Derivative (PID) controller are also presented. Furthermore, the DOA's performance is tested against five popular evolutionary algorithms. The results have shown that the DOA is highly competitive with other metaheuristics, beating them at the majority of the test functions.
Paper:
doi: 10.1155/2021/9107547
Citation pour cette source
Peraza-Vázquez, Hernán, Peña-Delgado, Adrián F., et.al. A Bio-Inspired Method for Engineering Design Optimization Inspired by Dingoes Hunting Strategies. Mathematical Problems in Engineering. (2021). Hindawi. https://doi.org/10.1155/2021/9107547
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Créé avec
R2018a
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DOA-code
Version | Publié le | Notes de version | |
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1.0.2 | Research paper online |
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1.0.1 | Paper available |
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1.0.0 |