Reptile Search Algorithm Considering Different Flight Heights to Solve Engineering Optimization Design Problems
The reptile search algorithm is an effective optimization method based on the natural laws of the biological world. By restoring and simulating the hunting process of reptiles, good optimization results can be achieved. However, due to the limitations of natural laws, it is easy to fall into local o...
Published in: | Biomimetics |
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Main Authors: | , , , , , |
Format: | Text |
Language: | English |
Published: |
Multidisciplinary Digital Publishing Institute
2023
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Subjects: | |
Online Access: | https://doi.org/10.3390/biomimetics8030305 |
_version_ | 1821661791887818752 |
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author | Liguo Yao Guanghui Li Panliang Yuan Jun Yang Dongbin Tian Taihua Zhang |
author_facet | Liguo Yao Guanghui Li Panliang Yuan Jun Yang Dongbin Tian Taihua Zhang |
author_sort | Liguo Yao |
collection | MDPI Open Access Publishing |
container_issue | 3 |
container_start_page | 305 |
container_title | Biomimetics |
container_volume | 8 |
description | The reptile search algorithm is an effective optimization method based on the natural laws of the biological world. By restoring and simulating the hunting process of reptiles, good optimization results can be achieved. However, due to the limitations of natural laws, it is easy to fall into local optima during the exploration phase. Inspired by the different search fields of biological organisms with varying flight heights, this paper proposes a reptile search algorithm considering different flight heights. In the exploration phase, introducing the different flight altitude abilities of two animals, the northern goshawk and the African vulture, enables reptiles to have better search horizons, improve their global search ability, and reduce the probability of falling into local optima during the exploration phase. A novel dynamic factor (DF) is proposed in the exploitation phase to improve the algorithm’s convergence speed and optimization accuracy. To verify the effectiveness of the proposed algorithm, the test results were compared with ten state-of-the-art (SOTA) algorithms on thirty-three famous test functions. The experimental results show that the proposed algorithm has good performance. In addition, the proposed algorithm and ten SOTA algorithms were applied to three micromachine practical engineering problems, and the experimental results show that the proposed algorithm has good problem-solving ability. |
format | Text |
genre | Northern Goshawk |
genre_facet | Northern Goshawk |
id | ftmdpi:oai:mdpi.com:/2313-7673/8/3/305/ |
institution | Open Polar |
language | English |
op_collection_id | ftmdpi |
op_doi | https://doi.org/10.3390/biomimetics8030305 |
op_relation | Biological Optimisation and Management https://dx.doi.org/10.3390/biomimetics8030305 |
op_rights | https://creativecommons.org/licenses/by/4.0/ |
op_source | Biomimetics Volume 8 Issue 3 Pages: 305 |
publishDate | 2023 |
publisher | Multidisciplinary Digital Publishing Institute |
record_format | openpolar |
spelling | ftmdpi:oai:mdpi.com:/2313-7673/8/3/305/ 2025-01-16T23:53:12+00:00 Reptile Search Algorithm Considering Different Flight Heights to Solve Engineering Optimization Design Problems Liguo Yao Guanghui Li Panliang Yuan Jun Yang Dongbin Tian Taihua Zhang 2023-07-11 application/pdf https://doi.org/10.3390/biomimetics8030305 eng eng Multidisciplinary Digital Publishing Institute Biological Optimisation and Management https://dx.doi.org/10.3390/biomimetics8030305 https://creativecommons.org/licenses/by/4.0/ Biomimetics Volume 8 Issue 3 Pages: 305 reptile search algorithm engineering optimization design northern goshawk optimization artificial vulture optimization algorithm Text 2023 ftmdpi https://doi.org/10.3390/biomimetics8030305 2023-09-03T23:52:58Z The reptile search algorithm is an effective optimization method based on the natural laws of the biological world. By restoring and simulating the hunting process of reptiles, good optimization results can be achieved. However, due to the limitations of natural laws, it is easy to fall into local optima during the exploration phase. Inspired by the different search fields of biological organisms with varying flight heights, this paper proposes a reptile search algorithm considering different flight heights. In the exploration phase, introducing the different flight altitude abilities of two animals, the northern goshawk and the African vulture, enables reptiles to have better search horizons, improve their global search ability, and reduce the probability of falling into local optima during the exploration phase. A novel dynamic factor (DF) is proposed in the exploitation phase to improve the algorithm’s convergence speed and optimization accuracy. To verify the effectiveness of the proposed algorithm, the test results were compared with ten state-of-the-art (SOTA) algorithms on thirty-three famous test functions. The experimental results show that the proposed algorithm has good performance. In addition, the proposed algorithm and ten SOTA algorithms were applied to three micromachine practical engineering problems, and the experimental results show that the proposed algorithm has good problem-solving ability. Text Northern Goshawk MDPI Open Access Publishing Biomimetics 8 3 305 |
spellingShingle | reptile search algorithm engineering optimization design northern goshawk optimization artificial vulture optimization algorithm Liguo Yao Guanghui Li Panliang Yuan Jun Yang Dongbin Tian Taihua Zhang Reptile Search Algorithm Considering Different Flight Heights to Solve Engineering Optimization Design Problems |
title | Reptile Search Algorithm Considering Different Flight Heights to Solve Engineering Optimization Design Problems |
title_full | Reptile Search Algorithm Considering Different Flight Heights to Solve Engineering Optimization Design Problems |
title_fullStr | Reptile Search Algorithm Considering Different Flight Heights to Solve Engineering Optimization Design Problems |
title_full_unstemmed | Reptile Search Algorithm Considering Different Flight Heights to Solve Engineering Optimization Design Problems |
title_short | Reptile Search Algorithm Considering Different Flight Heights to Solve Engineering Optimization Design Problems |
title_sort | reptile search algorithm considering different flight heights to solve engineering optimization design problems |
topic | reptile search algorithm engineering optimization design northern goshawk optimization artificial vulture optimization algorithm |
topic_facet | reptile search algorithm engineering optimization design northern goshawk optimization artificial vulture optimization algorithm |
url | https://doi.org/10.3390/biomimetics8030305 |