Improved Grey Wolf Optimization Algorithm and Application
This paper proposed an improved Grey Wolf Optimizer (GWO) to resolve the problem of instability and convergence accuracy when GWO is used as a meta-heuristic algorithm with strong optimal search capability in the path planning for mobile robots. We improved chaotic tent mapping to initialize the wol...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-05-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/22/10/3810 |
| _version_ | 1827666586457079808 |
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| author | Yuxiang Hou Huanbing Gao Zijian Wang Chuansheng Du |
| author_facet | Yuxiang Hou Huanbing Gao Zijian Wang Chuansheng Du |
| author_sort | Yuxiang Hou |
| collection | DOAJ |
| description | This paper proposed an improved Grey Wolf Optimizer (GWO) to resolve the problem of instability and convergence accuracy when GWO is used as a meta-heuristic algorithm with strong optimal search capability in the path planning for mobile robots. We improved chaotic tent mapping to initialize the wolves to enhance the global search ability and used a nonlinear convergence factor based on the Gaussian distribution change curve to balance the global and local searchability. In addition, an improved dynamic proportional weighting strategy is proposed that can update the positions of grey wolves so that the convergence of this algorithm can be accelerated. The proposed improved GWO algorithm results are compared with the other eight algorithms through several benchmark function test experiments and path planning experiments. The experimental results show that the improved GWO has higher accuracy and faster convergence speed. |
| first_indexed | 2024-03-10T01:52:44Z |
| format | Article |
| id | doaj.art-3a153e0db40a44b6a9b74fb88a0a3a9a |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T01:52:44Z |
| publishDate | 2022-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-3a153e0db40a44b6a9b74fb88a0a3a9a2023-11-23T13:01:38ZengMDPI AGSensors1424-82202022-05-012210381010.3390/s22103810Improved Grey Wolf Optimization Algorithm and ApplicationYuxiang Hou0Huanbing Gao1Zijian Wang2Chuansheng Du3School of Information and Electrical Engineering, Shandong Jianzhu University, Jinan 250101, ChinaSchool of Information and Electrical Engineering, Shandong Jianzhu University, Jinan 250101, ChinaSchool of Information and Electrical Engineering, Shandong Jianzhu University, Jinan 250101, ChinaSchool of Information and Electrical Engineering, Shandong Jianzhu University, Jinan 250101, ChinaThis paper proposed an improved Grey Wolf Optimizer (GWO) to resolve the problem of instability and convergence accuracy when GWO is used as a meta-heuristic algorithm with strong optimal search capability in the path planning for mobile robots. We improved chaotic tent mapping to initialize the wolves to enhance the global search ability and used a nonlinear convergence factor based on the Gaussian distribution change curve to balance the global and local searchability. In addition, an improved dynamic proportional weighting strategy is proposed that can update the positions of grey wolves so that the convergence of this algorithm can be accelerated. The proposed improved GWO algorithm results are compared with the other eight algorithms through several benchmark function test experiments and path planning experiments. The experimental results show that the improved GWO has higher accuracy and faster convergence speed.https://www.mdpi.com/1424-8220/22/10/3810Grey Wolf Optimizertent mappingconvergence factorpath planning |
| spellingShingle | Yuxiang Hou Huanbing Gao Zijian Wang Chuansheng Du Improved Grey Wolf Optimization Algorithm and Application Sensors Grey Wolf Optimizer tent mapping convergence factor path planning |
| title | Improved Grey Wolf Optimization Algorithm and Application |
| title_full | Improved Grey Wolf Optimization Algorithm and Application |
| title_fullStr | Improved Grey Wolf Optimization Algorithm and Application |
| title_full_unstemmed | Improved Grey Wolf Optimization Algorithm and Application |
| title_short | Improved Grey Wolf Optimization Algorithm and Application |
| title_sort | improved grey wolf optimization algorithm and application |
| topic | Grey Wolf Optimizer tent mapping convergence factor path planning |
| url | https://www.mdpi.com/1424-8220/22/10/3810 |
| work_keys_str_mv | AT yuxianghou improvedgreywolfoptimizationalgorithmandapplication AT huanbinggao improvedgreywolfoptimizationalgorithmandapplication AT zijianwang improvedgreywolfoptimizationalgorithmandapplication AT chuanshengdu improvedgreywolfoptimizationalgorithmandapplication |