Novel meta-heuristic bald eagle search optimisation algorithm
This study proposes a bald eagle search (BES) algorithm, which is a novel, nature-inspired meta-heuristic optimisation algorithm that mimics the hunting strategy or intelligent social behaviour of bald eagles as they search for fish. Hunting by BES is divided into three stages. In the first stage (s...
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| Published in: | The Artificial intelligence review Vol. 53; no. 3; pp. 2237 - 2264 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Dordrecht
Springer Netherlands
01.03.2020
Springer Springer Nature B.V |
| Subjects: | |
| ISSN: | 0269-2821, 1573-7462 |
| Online Access: | Get full text |
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| Abstract | This study proposes a bald eagle search (BES) algorithm, which is a novel, nature-inspired meta-heuristic optimisation algorithm that mimics the hunting strategy or intelligent social behaviour of bald eagles as they search for fish. Hunting by BES is divided into three stages. In the first stage (selecting space), an eagle selects the space with the most number of prey. In the second stage (searching in space), the eagle moves inside the selected space to search for prey. In the third stage (swooping), the eagle swings from the best position identified in the second stage and determines the best point to hunt. Swooping starts from the best point and all other movements are directed towards this point. BES is tested by adopting a three-part evaluation methodology that (1) describes the benchmarking of the optimisation problem to evaluate the algorithm performance, (2) compares the algorithm performance with that of other intelligent computation techniques and parameter settings and (3) evaluates the algorithm based on mean, standard deviation, best point and Wilcoxon signed-rank test statistic of the function values. Optimisation results and discussion confirm that the BES algorithm competes well with advanced meta-heuristic algorithms and conventional methods. |
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| AbstractList | This study proposes a bald eagle search (BES) algorithm, which is a novel, nature-inspired meta-heuristic optimisation algorithm that mimics the hunting strategy or intelligent social behaviour of bald eagles as they search for fish. Hunting by BES is divided into three stages. In the first stage (selecting space), an eagle selects the space with the most number of prey. In the second stage (searching in space), the eagle moves inside the selected space to search for prey. In the third stage (swooping), the eagle swings from the best position identified in the second stage and determines the best point to hunt. Swooping starts from the best point and all other movements are directed towards this point. BES is tested by adopting a three-part evaluation methodology that (1) describes the benchmarking of the optimisation problem to evaluate the algorithm performance, (2) compares the algorithm performance with that of other intelligent computation techniques and parameter settings and (3) evaluates the algorithm based on mean, standard deviation, best point and Wilcoxon signed-rank test statistic of the function values. Optimisation results and discussion confirm that the BES algorithm competes well with advanced meta-heuristic algorithms and conventional methods. |
| Audience | Academic |
| Author | Zaidan, B. B. Alsattar, H. A. Zaidan, A. A. |
| Author_xml | – sequence: 1 givenname: H. A. surname: Alsattar fullname: Alsattar, H. A. organization: Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris, Al-Rafidain University College – sequence: 2 givenname: A. A. surname: Zaidan fullname: Zaidan, A. A. email: aws.alaa@fskik.upsi.edu.my organization: Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris – sequence: 3 givenname: B. B. surname: Zaidan fullname: Zaidan, B. B. organization: Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris |
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| SubjectTerms | Algorithms Artificial Intelligence Bald eagle Birds Computation Computer Science Fish Heuristic Heuristic methods Hunting Intelligence Mathematical optimization Novels Optimization Optimization algorithms Performance evaluation Rank tests Searching Social behavior |
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| Title | Novel meta-heuristic bald eagle search optimisation algorithm |
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