Multiple Swarm Fruit Fly Optimization Algorithm Based Path Planning Method for Multi-UAVs
The path planning of unmanned aerial vehicles (UAVs) in the threat and countermeasure region is a constrained nonlinear optimization problem with many static and dynamic constraints. The fruit fly optimization algorithm (FOA) is widely used to handle this kind of nonlinear optimization problem. In t...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-04-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/10/8/2822 |
| _version_ | 1797570233319292928 |
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| author | Kunming Shi Xiangyin Zhang Shuang Xia |
| author_facet | Kunming Shi Xiangyin Zhang Shuang Xia |
| author_sort | Kunming Shi |
| collection | DOAJ |
| description | The path planning of unmanned aerial vehicles (UAVs) in the threat and countermeasure region is a constrained nonlinear optimization problem with many static and dynamic constraints. The fruit fly optimization algorithm (FOA) is widely used to handle this kind of nonlinear optimization problem. In this paper, the multiple swarm fruit fly optimization algorithm (MSFOA) is proposed to overcome the drawback of the original FOA in terms of slow global convergence speed and local optimum, and then is applied to solve the coordinated path planning problem for multi-UAVs. In the proposed MSFOA, the whole fruit fly swarm is divided into several sub-swarms with multi-tasks in order to expand the searching space to improve the searching ability, while the offspring competition strategy is introduced to improve the utilization degree of each calculation result and realize the exchange of information among various fruit fly sub-swarms. To avoid the collision among multi-UAVs, the collision detection method is also proposed. Simulation results show that the proposed MSFOA is superior to the original FOA in terms of convergence and accuracy. |
| first_indexed | 2024-03-10T20:22:00Z |
| format | Article |
| id | doaj.art-344cfba969f1447aa0a54ce83fde1ca7 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T20:22:00Z |
| publishDate | 2020-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-344cfba969f1447aa0a54ce83fde1ca72023-11-19T22:05:04ZengMDPI AGApplied Sciences2076-34172020-04-01108282210.3390/app10082822Multiple Swarm Fruit Fly Optimization Algorithm Based Path Planning Method for Multi-UAVsKunming Shi0Xiangyin Zhang1Shuang Xia2Faculty of Information Technology, Beijing University of Technology, Beijing 100124, ChinaFaculty of Information Technology, Beijing University of Technology, Beijing 100124, ChinaFaculty of Information Technology, Beijing University of Technology, Beijing 100124, ChinaThe path planning of unmanned aerial vehicles (UAVs) in the threat and countermeasure region is a constrained nonlinear optimization problem with many static and dynamic constraints. The fruit fly optimization algorithm (FOA) is widely used to handle this kind of nonlinear optimization problem. In this paper, the multiple swarm fruit fly optimization algorithm (MSFOA) is proposed to overcome the drawback of the original FOA in terms of slow global convergence speed and local optimum, and then is applied to solve the coordinated path planning problem for multi-UAVs. In the proposed MSFOA, the whole fruit fly swarm is divided into several sub-swarms with multi-tasks in order to expand the searching space to improve the searching ability, while the offspring competition strategy is introduced to improve the utilization degree of each calculation result and realize the exchange of information among various fruit fly sub-swarms. To avoid the collision among multi-UAVs, the collision detection method is also proposed. Simulation results show that the proposed MSFOA is superior to the original FOA in terms of convergence and accuracy.https://www.mdpi.com/2076-3417/10/8/2822multiple unmanned aerial vehicles (multi-UAVs)fruit fly optimization algorithm (FOA)path planningmulti-swarms |
| spellingShingle | Kunming Shi Xiangyin Zhang Shuang Xia Multiple Swarm Fruit Fly Optimization Algorithm Based Path Planning Method for Multi-UAVs Applied Sciences multiple unmanned aerial vehicles (multi-UAVs) fruit fly optimization algorithm (FOA) path planning multi-swarms |
| title | Multiple Swarm Fruit Fly Optimization Algorithm Based Path Planning Method for Multi-UAVs |
| title_full | Multiple Swarm Fruit Fly Optimization Algorithm Based Path Planning Method for Multi-UAVs |
| title_fullStr | Multiple Swarm Fruit Fly Optimization Algorithm Based Path Planning Method for Multi-UAVs |
| title_full_unstemmed | Multiple Swarm Fruit Fly Optimization Algorithm Based Path Planning Method for Multi-UAVs |
| title_short | Multiple Swarm Fruit Fly Optimization Algorithm Based Path Planning Method for Multi-UAVs |
| title_sort | multiple swarm fruit fly optimization algorithm based path planning method for multi uavs |
| topic | multiple unmanned aerial vehicles (multi-UAVs) fruit fly optimization algorithm (FOA) path planning multi-swarms |
| url | https://www.mdpi.com/2076-3417/10/8/2822 |
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